{ "session_id": "20260515_030312_135a25", "model": "deepseek-v4-pro", "base_url": "https://api.deepseek.com", "platform": "discord", "session_start": "2026-05-15T03:03:12.201785", "last_updated": "2026-05-15T03:13:13.858365", "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nHost: Linux (6.17.0-1011-oracle)\nUser home directory: /home/ubuntu\nCurrent working directory: /home/ubuntu/.hermes/hermes-agent\n\nYou are in a Discord server or group chat communicating with your user. You can send media files natively: include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) are sent as photo attachments, audio as file attachments. You can also include image URLs in markdown format ![alt](url) and they will be sent as attachments.\n\nConversation started: Friday, May 15, 2026 03:03 AM\nModel: deepseek-v4-pro\nProvider: deepseek", "tools": [ { "type": "function", "function": { "name": "mcp_context7_query_docs", "description": "Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.\n\nYou must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nDo not call this tool more than 3 times per question.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "libraryId": { "type": "string", "description": "Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'." }, "query": { "type": "string", "description": "The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query." } }, "required": [ "libraryId", "query" ] } } }, { "type": "function", "function": { "name": "mcp_context7_resolve_library_id", "description": "Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.\n\nYou MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nEach result includes:\n- Library ID: Context7-compatible identifier (format: /org/project)\n- Name: Library or package name\n- Description: Short summary\n- Code Snippets: Number of available code examples\n- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)\n- Benchmark Score: Quality indicator (100 is the highest score)\n- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.\n\nFor best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.\n\nSelection Process:\n1. Analyze the query to understand what library/package the user is looking for\n2. Return the most relevant match based on:\n- Name similarity to the query (exact matches prioritized)\n- Description relevance to the query's intent\n- Documentation coverage (prioritize libraries with higher Code Snippet counts)\n- Source reputation (consider libraries with High or Medium reputation more authoritative)\n- Benchmark Score: Quality indicator (100 is the highest score)\n\nResponse Format:\n- Return the selected library ID in a clearly marked section\n- Provide a brief explanation for why this library was chosen\n- If multiple good matches exist, acknowledge this but proceed with the most relevant one\n- If no good matches exist, clearly state this and suggest query refinements\n\nFor ambiguous queries, request clarification before proceeding with a best-guess match.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "query": { "type": "string", "description": "The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query." }, "libraryName": { "type": "string", "description": "Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'." } }, "required": [ "query", "libraryName" ] } } }, { "type": "function", "function": { "name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "list", "poll", "log", "wait", "kill", "write", "submit", "close" ], "description": "Action to perform on background processes" }, "session_id": { "type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'." }, "data": { "type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)" }, "timeout": { "type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1 }, "offset": { "type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)" }, "limit": { "type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1 } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": { "type": "object", "properties": { "command": { "type": "string", "description": "The command to execute on the VM" }, "background": { "type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false }, "timeout": { "type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1 }, "workdir": { "type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory." }, "pty": { "type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false }, "notify_on_complete": { "type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false }, "watch_patterns": { "type": "array", "items": { "type": "string" }, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both." } }, "required": [ "command" ] } } }, { "type": "function", "function": { "name": "web_extract", "description": "Extract content from web page URLs. Returns page content in markdown format. Also works with PDF URLs (arxiv papers, documents, etc.) — pass the PDF link directly and it converts to markdown text. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.", "parameters": { "type": "object", "properties": { "urls": { "type": "array", "items": { "type": "string" }, "description": "List of URLs to extract content from (max 5 URLs per call)", "maxItems": 5 } }, "required": [ "urls" ] } } }, { "type": "function", "function": { "name": "web_search", "description": "Search the web for information. Returns up to 5 results by default with titles, URLs, and descriptions. The query is passed through to the configured backend, so operators such as site:domain, filetype:pdf, intitle:word, -term, and \"exact phrase\" may work when the backend supports them.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "The search query to look up on the web. You may include backend-supported operators such as site:example.com, filetype:pdf, intitle:word, -term, or \"exact phrase\"." }, "limit": { "type": "integer", "description": "Maximum number of results to return. Defaults to 5.", "minimum": 1, "maximum": 100, "default": 5 } }, "required": [ "query" ] } } } ], "message_count": 21, "messages": [ { "role": "user", "content": "Produce a final comprehensive markdown report on integrating Hermes Agent with health/fitness apps. Cover MacroFactor, MyFitnessPal, Fitbit, Google Health Connect, Google Fit, Hevy (already connected), Cronometer, and any health data aggregators.\n\nFor each app provide: API type, documentation URL, data accessible, authentication method, Python code skeleton, feasibility score (1-5), and cost.\n\nYou already have 12 web_search/extract results from the previous interrupted run — use those, extract the actual API doc pages now, and produce the FINAL deliverable. Don't re-search the same queries." }, { "role": "assistant", "content": "", "reasoning": "The user wants me to produce a comprehensive markdown report on integrating Hermes Agent with health/fitness apps. They mention I already have 12 web_search/extract results from a previous interrupted run, but I don't have access to those. Let me work with what I have and extract the actual API documentation pages for each app.\n\nLet me plan my approach:\n\n1. First, I need to gather API documentation for each app mentioned:\n - MacroFactor\n - MyFitnessPal\n - Fitbit\n - Google Health Connect\n - Google Fit\n - Hevy (already connected)\n - Cronometer\n - Health data aggregators\n\n2. For each, I need: API type, documentation URL, data accessible, authentication method, Python code skeleton, feasibility score (1-5), and cost.\n\nLet me start by extracting the actual API doc pages. I'll search for documentation pages and then extract them.", "finish_reason": "tool_calls", "reasoning_content": "The user wants me to produce a comprehensive markdown report on integrating Hermes Agent with health/fitness apps. They mention I already have 12 web_search/extract results from a previous interrupted run, but I don't have access to those. Let me work with what I have and extract the actual API documentation pages for each app.\n\nLet me plan my approach:\n\n1. First, I need to gather API documentation for each app mentioned:\n - MacroFactor\n - MyFitnessPal\n - Fitbit\n - Google Health Connect\n - Google Fit\n - Hevy (already connected)\n - Cronometer\n - Health data aggregators\n\n2. For each, I need: API type, documentation URL, data accessible, authentication method, Python code skeleton, feasibility score (1-5), and cost.\n\nLet me start by extracting the actual API doc pages. I'll search for documentation pages and then extract them.", "tool_calls": [ { "id": "call_00_o0hbBsWpsTS7sstexs0q0908", "call_id": "call_00_o0hbBsWpsTS7sstexs0q0908", "response_item_id": "fc_00_o0hbBsWpsTS7sstexs0q0908", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"MacroFactor API documentation developer\", \"limit\": 5}" } }, { "id": "call_01_1niJKb9Eg3sHsdqnq3wk9789", "call_id": "call_01_1niJKb9Eg3sHsdqnq3wk9789", "response_item_id": "fc_01_1niJKb9Eg3sHsdqnq3wk9789", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"MyFitnessPal API developer documentation 2024 2025\", \"limit\": 5}" } }, { "id": "call_02_hWvRnOl153J0yaBLa8W25941", "call_id": "call_02_hWvRnOl153J0yaBLa8W25941", "response_item_id": "fc_02_hWvRnOl153J0yaBLa8W25941", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"Fitbit Web API documentation dev.fitbit.com\", \"limit\": 5}" } }, { "id": "call_03_0HvtZVUqztaOjRUegznq0399", "call_id": "call_03_0HvtZVUqztaOjRUegznq0399", "response_item_id": "fc_03_0HvtZVUqztaOjRUegznq0399", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"Google Health Connect API cloud sync REST access developer\", \"limit\": 5}" } }, { "id": "call_04_hMalfW1uDhThEbnfEu2k5242", "call_id": "call_04_hMalfW1uDhThEbnfEu2k5242", "response_item_id": "fc_04_hMalfW1uDhThEbnfEu2k5242", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"Google Fit REST API documentation developers.google.com/fit\", \"limit\": 5}" } } ] }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://github.com/sjawhar/macrofactor/blob/main/docs/api-reference.md\",\n \"title\": \"docs/api-reference.md at main · sjawhar/macrofactor\",\n \"description\": \"# File: sjawhar/macrofactor/docs/api-reference.md\\n[...]\\n```md\\n# MacroFactor API Reference\\n[...]\\nMacroFactor (by Stronger By Science) uses a shared Firebase backend for both its Nutrition and Workouts apps. This document details the reverse-engineered API schema based on the Firestore REST API.\\n[...]\\n## Architecture & Authentication\\n[...]\\n- **Firebase Project**: `sbs-diet-app`\\n- **Base URL**: `https://firestore.googleapis.com/v1/projects/sbs-diet-app/databases/(default)/documents`\\n- **Auth Endpoint**: `https://identitytoolkit.googleapis.com/v1/accounts:signInWithPassword?key={API_KEY}`\\n- **Token Refresh**: `https://securetoken.googleapis.com/v1/token?key={API_KEY}`\\n[...]\\nThe API uses standard Firebase Identity Toolkit. Exchanging email/password yields an `idToken` (JWT) which must be passed as `Authorization: Bearer ` to Firestore endpoints. Both `com.sbs.diet` and `com.sbs.train` bundle IDs work.\\n[...]\\nID Scheme & Exercise Database\\n[...]\\nHowever, the complete reference database is bundled within the workout app APK as `app_file.json`. This JSON contains a `uuidIndex` that acts as a universal dictionary, mapping all 4,170 hex IDs in the system to their human-readable names and types. Our TypeScript client resolves these locally.\\n[...]\\n## Collections Reference\\n[...]\\nAll user data is stored under the `users/{uid}/` prefix.\\n[...]\\n**Path:** `users/{uid}/\\n[...]\\nHistory/{uuid}`\\n[...]\\n**Path:** `users/{uid}/gym/{uuid}`\\n[...]\\n**Type:** Collection of user\\n[...]\\n**Path:** `users/{uid}/food/{YYYY-MM-DD}`\\n[...]\\n**Type:** Document containing all\\n[...]\\nentries for a specific\\n[...]\\n### Daily Nutrition Summaries\\n[...]\\n**Path:** `users/{uid}/nutrition/{YYYY}`\\n[...]\\n**Type:** Document containing daily summaries for an entire year.\\n**Structure:** Map where keys are `MMDD`.\\n[...]\\n### Scale /\\n[...]\\n**Path:** `users/{uid}/scale/{YYYY}`\\n[...]\\n**Type:** Document containing daily weight entries for a year.\\n[...]\\n**Structure:**\\n[...]\\n**Path:** `users/{uid}/steps/{YYYY}`\\n[...]\\n**Path:** `users/{uid}/customExercises/{uuid}`\\n[...]\\n**Path:** `users/{uid}/trainingProgram/{programId}`\\n[...]\\n### Workout Profile\\n[...]\\n**Path:** `users/{uid}/profiles/workout`\\n**Type:** Single document with workout app settings\\n[...]\\nKey fields:\\n[...]\\nactiveProgramId` —\\n[...]\\n-exercise settings (weight unit, bar weight, notes)\\n[...]\\nuseDeload`, `rirTracking` — Program execution settings\\n[...]\\n### Diet Profile\\n[...]\\n**Path:** `users/{uid}/profiles/diet`\\n[...]\\n**Type:** Single document with diet app toolbar/shortcut config\",\n \"position\": 1\n },\n {\n \"url\": \"https://github.com/sjawhar/macrofactor\",\n \"title\": \"sjawhar/macrofactor\",\n \"description\": \"# MacroFactor CLI & API Client\\n[...]\\nA TypeScript client and CLI for interacting with MacroFactor programmatically — the nutrition and workout tracker by Stronger By Science.\\n[...]\\n## CLI commands\\n[...]\\n| Command | Description |\\n| --- | --- |\\n| `\\n[...]\\n` | List recent workouts with exercise/set counts |\\n| `\\n[...]\\n| Full detail for a specific\\n[...]\\n|\\n| `\\n[...]\\nexercise database |\\n| `\\n[...]\\n|\\n| `\\n[...]\\n|\\n| `\\n[...]\\n| `\\n[...]\\n| `log\\n[...]\\n`log-\\n[...]\\n## Programmatic usage\\n[...]\\n```typescript\\nimport { MacroFactorClient } from './src/lib/api/index';\\nimport { resolve\\n[...]\\n} from './src/lib/api/exercises';\\n[...]\\nThe MacroFactor app uses a Firebase/Firestore backend (`sbs-diet-app`). This client talks directly to the Firestore REST API using standard Firebase authentication.\\n[...]\\n- **User data** (workouts, food logs, weight, etc.) is read/write accessible via Firestore REST with a valid auth token\\n- **Reference data** (exercises, muscles, equipment) is locked behind Firebase App Check and returns 403 — this client resolves them locally using a bundled JSON database extracted from the app\\n- **Food search** uses MacroFactor's Typesense instance, which combines USDA common foods with a branded food database\\n[...]\\nSee `docs/api-reference.md` for the full Firestore schema.\\n[...]\\n## MCP server\\n[...]\\nThis project includes an MCP (Model Context Protocol) server that exposes the MacroFactor API as tools for AI agents like Claude, Cursor, and Windsurf. Use it to integrate MacroFactor data and operations into your AI workflows.\\n[...]\\n### Available tools\\n[...]\\nThe MCP server exposes 28 tools for reading and writing MacroFactor data:\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get_workouts` | List recent workouts with exercise/set counts |\\n| `get_workout` | Full detail for a specific workout (UUID) |\\n| `get_food_log` | Show food log for a date (default: today) |\\n| `search_foods` | Search the food database without logging |\\n| `get_nutrition` | Get nutrition summary for a date |\\n| `get_weight_log` | List weight entries for a date range |\\n| `get_profile` | Show user profile and preferences |\\n| `get_gyms` | List gym profiles |\\n| `search_exercises` | Search the bundled exercise database |\\n| `resolve_exercise` | Resolve a hex ID to exercise name + muscles |\\n| `resolve_muscle` | Resolve a hex ID to muscle name |\\n| `resolve_equipment` | Resolve a hex ID to equipment name |\\n[...]\\n#### Write tools\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `log_food` | Search and log a food entry |\\n| `log_food_by_id` | Log a food entry by ID (skip search) |\\n| `update_food_entry` | Update a food entry quantity |\\n| `delete_food_entry` | Delete a food entry |\\n| `log_weight` | Log a scale entry |\\n| `log_workout` | Create a workout with exercises |\\n| `log_exercise` | Add exercises to an existing workout |\\n| `update_workout_set` | Update a workout set (reps, weight, rest) |\\n| `delete_workout_set` | Delete a workout set |\\n| `create_custom_exercise` | Create a custom exercise in a gym profile |\\n| `update_custom_exercise` | Update a custom exercise |\\n| `delete_custom_exercise` | Delete a custom exercise |\\n| `create_gym_profile` | Create a new gym profile |\\n| `update_gym_profile` | Update a gym profile |\\n| `delete_gym_profile` | Delete a gym profile |\\n| `update_user_preferences` | Update user preferences (targets, macros, etc.) |\\n[...]\\n## Project structure\\n[...]\\nhelpers.ts JSON input parsing, set expansion, weight conversion\\n helpers.test.ts Tests for CLI helpers\\n[...]\\nsrc/lib/api/\\n auth.ts Firebase auth (sign-in, token refresh)\\n client.ts MacroFactorClient class (all read/write methods)\\n firestore.ts Firestore REST helpers + food entry type safety\\n typesense.ts Food search via Typesense\\n exercises.ts Local exercise database resolver\\n types.ts Shared TypeScript types\\n workout-types.ts Workout-specific types\\n[...]\\ndocs/\\n api-reference.md Full Firestore schema documentation\",\n \"position\": 2\n },\n {\n \"url\": \"https://crates.io/crates/macro-factor-api\",\n \"title\": \"macro-factor-api v0.4.0\",\n \"description\": \"# macro-factor-api v0.4.0\\n[...]\\nUnofficial Rust client for reading MacroFactor data\\n[...]\\n- Repository: https://github.com/benthecarman/macro-factor-api\\n[...]\\nhecarman\\n[...]\\n# macro-factor-rs\\n[...]\\nUnofficial Rust client library for reading MacroFactor data via the Firestore REST API.\\n[...]\\n### Email/Password (recommended)\\n[...]\\nAdd a password to your MacroFactor account, then sign in directly:\\n[...]\\nlet mut client = MacroFactorClient::login(\\\"email\\\", \\\"password\\\").await?;\\n[...]\\n### Refresh Token\\n[...]\\n```rust\\nlet mut client = MacroFactorClient::new(\\\"your_refresh_token\\\".to_string());\\n[...]\\n```rust\\nuse macro_factor_api::client::MacroFactorClient;\\nuse chrono::NaiveDate;\\n[...]\\n#[tokio::main]\\nasync fn main() -> anyhow::Result<()> {\\n let mut client = MacroFactorClient::login(\\\"email\\\", \\\"password\\\").await?;\\n\\n // Get user profile\\n let profile = client.get_profile().await?;\\n[...]\\n// Get weight entries\\n let start = NaiveDate::from_ymd_opt(2025, 1, 1).unwrap();\\n let end = NaiveDate::from_ymd_opt(2025, 1, 31).unwrap();\\n let weights = client.get_weight_entries(start, end).await?;\\n\\n // Get nutrition summaries\\n let nutrition = client.get_nutrition(start, end).await?;\\n\\n // Get food log for a specific day\\n let foods = client.get_food_log(start).await?;\\n\\n // Get step counts\\n let steps = client\\n[...]\\nget_steps(start, end).await?;\\n\\n Ok(())\\n}\\n[...]\\n## API Methods\\n[...]\\n`login(email, password)`\\n[...]\\nSign in with email/password\\n[...]\\n`new(refresh_token)`\\n[...]\\nCreate client with a refresh token\\n[...]\\n`get_profile()`\\n[...]\\nUser profile (name, height, weight units, goals, etc.)\\n[...]\\n`get_goals()`\\n\\nCurrent calorie/macro targets and TDEE\\n[...]\\n`get_weight_entries(start, end)`\\n[...]\\nScale entries with weight in kg\\n[...]\\n`get_nutrition(start, end)`\\n[...]\\nDaily summaries (calories, protein, carbs, fat, sugar, fiber)\\n[...]\\n`get_food_log(date)`\\n[...]\\nIndividual food entries for a day\\n[...]\\n`get_steps(start, end)`\\n\\nDaily step counts\\n[...]\\n`log_food(date, name, cal, protein, carbs, fat)`\\n[...]\\nLog a food entry\\n[...]\\n`log_weight(date, weight_kg, body_fat)`\\n[...]\\nLog a weight entry\\n[...]\\n`log_nutrition(date, cal, protein, carbs, fat)`\\n[...]\\nLog a nutrition summary\\n[...]\\n`get_raw_document(path)`\\n[...]\\nFetch any Firestore document by path\\n[...]\\n## Firestore Schema\\n[...]\\nData lives under `users/{uid}/`:\\n[...]\\n- **`scale/{year}`** — weight entries keyed by `MMDD`\\n- **`nutrition/{year}`** — daily macro summaries keyed by `MMDD`\\n- **`food/{YYYY-MM-DD}`** — food log entries per day\\n- **`steps/{year}`** — step counts keyed by `MMDD`\\n- **`body/{year}`** — body measurements keyed by `MMDD`\\n- **`customFoods/{id}`** — user-created foods and recipes\",\n \"position\": 3\n },\n {\n \"url\": \"https://docs.rs/macro-factor-api/latest/macro_factor_api/all.html\",\n \"title\": \"List of all items in this crate\",\n \"description\": \"List of all items in this crate\\n[...]\\nSkip to main content\\n\\n# List of all items\\n\\n### Structs\\n\\n### Functions\\n[...]\\n### Constants\\n\\nList of all items in this crate\\n\\nDocs.rs\\n\\n* macro-factor-api-0.4.0\\n\\n*\\nmacro-factor-api 0.4.0\\n* Permalink\\n\\n* Docs.rs crate page\\n\\n* MIT\\n* Links\\n* Repository\\n\\n* crates.io\\n\\n* Source\\n\\n* Owners\\n* benthecarman\\n\\n* Dependencies\\n*\\n*\\n[...]\\n* The\\n[...]\\n* Standard Library API\\n[...]\\n* Rust by\\n[...]\\n* The\\n[...]\\nppy Documentation\\nSkip to main content## All\\n# List of all items\\n[...]\\n### Structs\\n[...]\\n* auth::FirebaseAuth\\n* client::MacroFactorClient\\n* firestore::Document\\n* firestore::FirestoreClient\\n* models::FoodEntry\\n* models::FoodServing\\n* models::Goals\\n* models::NutritionSummary\\n* models::ScaleEntry\\n* models::SearchFoodResult\\n* models::StepEntry\\n* models::UserProfile### Functions\\n* firestore::parse\\\\_document\\n* firestore::parse\\\\_firestore\\\\_fields\\n* firestore::parse\\\\_firestore\\\\_value\\n* firestore::to\\\\_firestore\\\\_fields\\n* firestore::to\\\\_firestore\\\\_value### Constants\\n* auth::PROJECT\\\\_ID\",\n \"position\": 4\n },\n {\n \"url\": \"https://registry.npmjs.org/@sjawhar/macrofactor-mcp\",\n \"title\": \"@sjawhar/macrofactor-mcp\",\n \"description\": \"A TypeScript client and CLI for interacting with MacroFactor programmatically — the nutrition and workout tracker by Stronger By Science.\\n[...]\\n# MacroFactor CLI & API Client\\n[...]\\nA TypeScript client and CLI for interacting with MacroFactor programmatically — the nutrition and workout tracker by Stronger By Science.\\n[...]\\n- **Read** your\\n[...]\\nhistory, food logs, weight entries,\\n[...]\\nsummaries, gym profiles, and custom exercises\\n- **Write** food log entries, create new workouts, update existing\\n[...]\\nsets, and log\\n[...]\\n- **Search** the MacroFactor food database (common foods + branded items via Typesense)\\n- **Resolve** the opaque 32-character hex IDs used for exercises, muscles, and equipment to human-readable names using the bundled reference database\\n[...]\\n## CLI commands\\n[...]\\n| Command | Description |\\n| --- | --- |\\n| `\\n[...]\\n` | List recent\\n[...]\\nwith exercise/set counts |\\n| `\\n[...]\\n| Full detail for a specific\\n[...]\\n|\\n| `\\n[...]\\ndatabase |\\n| `\\n[...]\\n|\\n| `\\n[...]\\n|\\n| `\\n[...]\\n| `log\\n[...]\\n) |\\n| `log\\n[...]\\nJSON input) |\\n| `log-\\n[...]\\n'{JSON}'` |\\n[...]\\nJSON input) |\\n| `log-\\n[...]\\n) |\\n| `\\n[...]\\n## Programmatic usage\\n[...]\\nThe MacroFactor app uses a Firebase/Firestore backend (`sbs-diet-app`). This client talks directly to the Firestore REST API using standard Firebase authentication.\\n[...]\\nuses MacroFactor\\n[...]\\n## MCP server\\n[...]\\nThis project includes an MCP (Model Context Protocol) server that exposes the MacroFactor API as tools for AI agents like Claude, Cursor, and Windsurf. Use it to integrate MacroFactor data and operations into your AI workflows.\\n[...]\\n### Available tools\\n[...]\\nThe MCP server exposes 28 tools for reading and writing MacroFactor data:\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get_workouts` | List recent workouts with exercise/set counts |\\n| `get_workout` | Full detail for a specific workout (UUID) |\\n| `get_food_log` | Show food log for a date (default: today) |\\n| `search_foods` | Search the food database without logging |\\n| `get_nutrition` | Get nutrition summary for a date |\\n| `get_weight_log` | List weight entries for a date range |\\n| `get_profile` | Show user profile and preferences |\\n| `get_gyms` | List gym profiles |\\n| `search_exercises` | Search the bundled exercise database |\\n| `resolve_exercise` | Resolve a hex ID to exercise name + muscles |\\n| `resolve_muscle` | Resolve a hex ID to muscle name |\\n| `resolve_equipment` | Resolve a hex ID to equipment name |\\n[...]\\n#### Write tools\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `log_food` | Search and log a food entry |\\n| `log_food_by_id` | Log a food entry by ID (skip search) |\\n| `update_food_entry` | Update a food entry quantity |\\n| `delete_food_entry` | Delete a food entry |\\n| `log_weight` | Log a scale entry |\\n| `log_workout` | Create a workout with exercises |\\n| `log_exercise` | Add exercises to an existing workout |\\n| `update_workout_set` | Update a workout set (reps, weight, rest) |\\n| `delete_workout_set` | Delete a workout set |\\n| `create_custom_exercise` | Create a custom exercise in a gym profile |\\n| `update_custom_exercise` | Update a custom exercise |\\n| `delete_custom_exercise` | Delete a custom exercise |\\n| `create_gym_profile` | Create a new gym profile |\\n| `update_gym_profile` | Update a gym profile |\\n| `delete_gym_profile` | Delete a gym profile |\\n| `update_user_preferences` | Update user preferences (targets, macros, etc.) |\\n[...]\\n## Project structure\\n[...]\\nhelpers.ts JSON\\n[...]\\nhelpers.\\n[...]\\n.ts Tests for\\n[...]\\nsrc/lib/api/\\n auth.ts Firebase auth (sign-in, token refresh)\\n client.ts MacroFactorClient class (all read/write methods)\\n firestore.ts Firestore REST helpers + food entry type safety\\n typesense.ts Food search via Typesense\\n exercises.ts Local exercise database resolver\\n types.ts Shared TypeScript types\\n workout-types.ts Workout-specific types\\n[...]\\ndocs/\\n api-reference.md Full Firestore schema documentation\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_00_o0hbBsWpsTS7sstexs0q0908" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://myfitnesspalapi.com/docs/\",\n \"title\": \"Health, nutrition, and wellness - MyFitnessPal API\",\n \"description\": \"MFP API - MFP API\\n\\n# Health, nutrition, and wellness\\n\\nWe follow a RESTful approach to designing our APIs. Requests and responses use JSON in a familiar REST style. Clients use standard HTTP methods – POST, GET, PUT, DELETE, to update resources. You can get a quick overview of our APIs before you get started.\",\n \"position\": 1\n },\n {\n \"url\": \"https://myfitnesspalapi.com/\",\n \"title\": \"MyFitnessPal API\",\n \"description\": \"MFP API - Home\\n\\nMake An Impact\\n\\n## Get Started\\n\\nWe are not accepting requests for API access at this time.\\n\\nAPI\\n\\nRESTful interfaces.\\n\\nMFP API - Home\\n\\n#\\nMyFitnessPal\\n\\nMenu\\n\\nMake An\\n**Impact**\\n## Get Started\\nWe are not accepting requests for API access at this time.\\n**API**\\nRESTful interfaces.\\nExplore\",\n \"position\": 2\n },\n {\n \"url\": \"https://myfitnesspalapi.com/faq/\",\n \"title\": \"MFP API - Developer FAQ\",\n \"description\": \"MFP API - Developer FAQ\\n[...]\\n## Developer FAQ\\n[...]\\n# Developer FAQ\\n[...]\\nWhat Features Does The MFP API Have?\\n[...]\\nPlease refer to the MFP documentation found here. All information about accessible data is documented for your reference.\\n[...]\\nOur standard API accounts have a max 25,000 requests/day and 60 requests/second. If you would like to increase your requests (quota or rate limit increase), please contact our support team and we will get back with you. Please list in your ticket: How many requests you need, what company you work for, and the purpose for extended access.\\n[...]\\nDo You Have API Examples Available?\\n[...]\\nIf you are interested in seeing MFP API examples, visit Github:\\n[...]\\nMake sure your OAuth2 request includes an “Api-Key” header with your client ID and that your request is using the host https://oauth2-api.myfitnesspal.com.\\n[...]\\nRequest For Enterprise API Access\\n[...]\\nIf you need Enterprise API, put your request here. We will need: company, application, target audience, scale of use (requests per second and expected number of requests per day).\\n[...]\\nSDKs In Platforms Other\\n[...]\\nNo, not at this time. Check back here for future enhancements or consider signing up for an Enterprise account for access to special features.\\n[...]\\nConsumers with an Enterprise\\n[...]\\nmay have higher request limits. An Enterprise account is probably best if you anticipate a large user group. Features are basically the same between the two.\",\n \"position\": 3\n },\n {\n \"url\": \"https://myfitnesspalapi.com/docs/partner-authentication/\",\n \"title\": \"MFP API - MyFitnessPal Developer - Partner Authentication\",\n \"description\": \"MFP API - MyFitnessPal Developer - Partner Authentication\\n[...]\\n# Partner Authentication\\n[...]\\nMyFitnessPal API partners are provided with two pieces of information used for authorizing and authenticating API requests: a “client id” and a “client secret”. The client id serves to uniquely identify a partner application. The client secret is used during the authentication process to ensure that the partner application is issuing API calls and not a third party that happens to guess the partner client id.\\n[...]\\nIn terms of security, the client id should be considered public, and the client secret private. Make sure that the client secret is securely protected. Never pass it in plaintext over the Internet. Do not be concerned about keeping the client id private.\",\n \"position\": 4\n },\n {\n \"url\": \"https://myfitnesspalapi.com/docs/request-query-parameters/\",\n \"title\": \"MFP API - MyFitnessPal Developer - Request query parameters\",\n \"description\": \"MFP API - MyFitnessPal Developer - Request query parameters\\n[...]\\n# Authorization Code Grant\\n[...]\\nThis is the first step in the process, the granting of a single-use authorization code.\\n[...]\\nGET ​/oauth2/auth\\n[...]\\n## Request Query Parameters\\n[...]\\n| Name | Description | Required |\\n| --- | --- | --- |\\n| response_type | Indicates the desired response type. Must be set to ​code​. | Y |\\n| client_id | Your app’s client id | Y |\\n| redirect_uri | The URL to redirect to when the user completes the authorization flow. This URL will receive the results of the authorization request as query parameters. | Y |\\n| scope | A space­delimited list of permission scopes requested by your app. Must be limited to scopes that have not previously been authorized. (See below for a list of scope.) | Y |\\n[...]\\n| state | An opaque string used to maintain state between requests. MyFitnessPal will include this string unchanged as a query parameter appended to ​redirect_uri​. Useful for protecting against Cross-site Request Forgery (CSRF) attacks. If used, it should be an arbitrary string unique to each authentication request. | N |\\n[...]\\nAvailable permission scopes:\\n[...]\\n```\\n ● measurements\\n ● diary\\n ● private­exercises \\n ● subscriptions\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_01_1niJKb9Eg3sHsdqnq3wk9789" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/explore/\",\n \"title\": \"Swagger UI - Fitbit\",\n \"description\": \"Swagger UI\\n\\nSwagger UI\",\n \"position\": 1\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/developer-guide\",\n \"title\": \"Developer Guide\",\n \"description\": \"Developer Guide \\n\\n# Fitbit Web API Developer Guide\\n[...]\\nThe Fitbit Web API Developer Guide is intended to help a developer get started using the the Web API, along with providing additional content on implementing the endpoints. Anyone may use the Web API to build integrations with the Fitbit data services, so long as their application complies with:\\n[...]\\nThis guide provides the following resources,\\n[...]\\n- Getting Started explains how to create a Fitbit developer account and register an application.\\n[...]\\n- Authorization steps you through implementing the Authorization Code Grant Flow with PKCE; the recommended authorization flow for requesting access to Fitbit user data.\\n[...]\\n- Application Design contains various topics to consider when building your application, such as data types, headers, localization, the rate limit, etc.\\n[...]\\n- Libraries and Sample Code provides a list of OAuth2 libraries and sample code our developer community found and has successfully used.\\n[...]\\nIf you have problems using the Web APIs, check out the Troubleshooting Guide for a solution before contacting the Web API Developer Support team.\",\n \"position\": 2\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/authorization\",\n \"title\": \"Authorization\",\n \"description\": \"The Authorization endpoints allow an application to onboard Fitbit users who want to share their data with the specified application. The application can initiate the consent flow for new users, obtain the access token and refresh tokens, validate the tokens, and revoke consent to the user.\\n[...]\\nFitbit supports OAuth 2.0. The authorization models we support are Authorization Code Grant Flow, Authorization Code Grant Flow with PKCE and Implicit Grant Flow. We recommend Authorization Code Grant Flow with PKCE, and our examples demonstrate how to set it up. Client Credentials is supported but does not allow the retrieval of user data. It works only with the Fitbit Commerce APIs.\\n[...]\\nThe endpoints available in this section are\\n[...]\\n- Authorize initiates the OAuth 2.0 authorization flow by presenting the consent screen to the Fitbit user.\\n[...]\\n- Client Credentials initiates the Client Credentials Grant flow. This authorization flow does not support retrieving Fitbit user data.\\n[...]\\n- Introspect allows the application to retrieve the active state of an OAuth 2.0 token.\\n[...]\\n- OAuth2 Token exchanges the authorization code for the initial access token and refresh token.\\n[...]\\n- Refresh Token creates a new access token and refresh token for a user when the existing access token has expired.\\n- Revoke Token disables a user's authorization and all associated tokens.\",\n \"position\": 3\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/activity\",\n \"title\": \"Activity\",\n \"description\": \"The Activity endpoints are used to query and/or modify a Fitbit user's daily activity data. The information returned is the step count, distance, elevation, floors, calories burned, active minutes, activity goals, exercise details, etc. The Activity endpoints support returning Intraday data (see Intraday).\\n[...]\\nThe endpoints available in this section are\\n[...]\\n- Get Activity Goals retrieves a user's daily or weekly activity goals.\\n[...]\\n- Get Activity Log List retrieves a list of the user's recorded activities, and the activity details.\\n[...]\\n- Get Activity Type retrieves the details for a single activity from the\\n[...]\\n- Get All Activity Types retrieves the details for all activities from the Fitbit activities database.\\n[...]\\n- Get Daily Activity Summary retrieves a summary of\\n[...]\\nuser's activity for\\n[...]\\nGet Recent Activity Types\",\n \"position\": 4\n },\n {\n \"url\": \"https://www.fitbit.com/dev\",\n \"title\": \"API Documents\",\n \"description\": \"Fitbit\\n\\n- Visit Dev Forum\\n- Read API Docs\\n\\n## Fitbit Logos\\n\\nDownload our logos and read trademark guidelines and terms of service\\n\\n## Get affiliated\\n\\nBecome a Fitbit Affiliate and make money from your users who buy a Fitbit.\\n\\n# Welcome. It's an API\\n\\nThe Fitbit API allows developers to interact with Fitbit data in their own applications, products and services.\\n\\nThe API allows for most of the read and write methods that you will need to support your application. If you have uses or needs that are not currently supported by the API, drop by the Dev Forum and let us know! We look forward to working closely with the development community to make the Fitbit API a system that enables you to do awesome, mind blowing stuff.\\n\\n# API Documents\\n\\nInterested in making or integrating apps with Fitbit? Check out the API wiki for details and documentation to help you get started.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_02_hWvRnOl153J0yaBLa8W25941" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://developers.google.com/health/endpoints\",\n \"title\": \"Endpoints  |  Google Health API  |  Google for Developers\",\n \"description\": \"This page provides an overview of REST API conventions, along with an index of\\ncommon Google Health API tasks and examples of each.\\n[...]\\n## REST API conventions\\n[...]\\nThe Google Health API follows the Google API Improvement Proposals\\n(AIP)\\nstandards, specifically AIP-127 (HTTP and gRPC Transcoding) and AIP-131 through\\nAIP-135 (Standard Methods). These standards define how data is mapped from a\\nproto message to an HTTP request.\\n[...]\\nQuery parameters are used when the data is part of the URL. This is primarily\\nfor `GET` requests (fetching a resource) or `LIST` requests\\n(filtering/pagination), but is also used for `DELETE` operations.\\n[...]\\nThe request body is used when the data modifies the state of a resource or is\\ntoo large for a URL. The body is usually a JSON representation of the resource\\nitself. Typically used for `POST`, `PATCH`, and `PUT` operations.\\n[...]\\nIn an AIP-134 compliant `Update` method, or a `PATCH` operation, both are used.\\nThe URL contains the\\nresource name, the body contains the updated resource data, and a query\\nparameter (usually `update_mask`) specifies which fields to change.\\n[...]\\nExecuting the Google Health API endpoints requires using the appropriate headers\\nand access token. The following header is recommended for both GET and POST\\nrequests:\\n[...]\\n```\\nAuthorization: Bearer access-token\\nAccept: application/json\\n\\n```\\n[...]\\n## API task index\\n[...]\\nThis section provides an index of common Google Health API tasks and examples of\\neach.\\n[...]\\nAfter a user consents through Google OAuth 2.0, the token response does not\\ncontain the Fitbit or Google user ID. To obtain the user ID, call the\\n`getIdentity` endpoint. `getIdentity`\\nreturns both the Fitbit legacy user ID and the Google user ID.\\n[...]\\nWe recommend that as soon as a new user consents through OAuth, you call the\\n`getIdentity` endpoint and store both user IDs. This provides backward and\\nforward compatibility in your integration.\\n[...]\\n```\\nGET https://health.googleapis.com/v4/users/me/identity\\n[...]\\nAuthorization: Bearer access-token\\nAccept: application/json\\n[...]\\ndata collected throughout\\n[...]\\nsupported intervals for that data type\\n[...]\\n### Filter data by an interval civil start time\\n[...]\\nUse the `list` endpoint with a `filter` parameter to filter data by civil time\\nor an interval.\\n[...]\\n### Filter data by data sources such as wearables\\n[...]\\nUse the `reconcile`\\nendpoint to get\\ndata by a \\\"data source family\\\" in a reconciled stream.\\n[...]\\n### Aggregate data points over a range of time\\n[...]\\nUse the `rollUp`\\nendpoint to return the\\naggregate of data points based on a window in seconds, over the `datetime` range\\nbased on the users physical time (in UTC).\\n[...]\\nrollUp` endpoint, you\\n[...]\\nthe required date range in\\n[...]\\nuser's civil time. For example:\\n[...]\\n### Aggregate data across a single day or multiple days\\n[...]\\nThe `dailyRollUp`\\nendpoint should be\\nused when you want to aggregate data across\\na single day or multiple days, known as `windowSize`. Provide the closed-open\\ncivil time range for the required interval in the request body. Depending on the\\ndata type, you will either receive the sum or the average over the interval.\\n[...]\\n### Insert or update a user's health data\\n[...]\\nUse the `patch`\\nendpoint to insert or\\nupdate a user's Fitbit app data.\\n[...]\\n### Delete user health data\\n[...]\\nUse the `batchDelete`\\nendpoint to delete\\nan array of a user's Fitbit app data.\",\n \"position\": 1\n },\n {\n \"url\": \"https://android-dot-devsite-v2-prod.appspot.com/health-and-fitness/health-connect/sync-data\",\n \"title\": \"Synchronize data  |  Android health & fitness  |  Android Developers\",\n \"description\": \"This guide is compatible with Health Connect version 1.1.0-alpha12.\\n[...]\\nMost apps that integrate with Health Connect have their own datastore that serves as the source of truth. Health Connect provides ways to keep your app in sync.\\n[...]\\n- Feed new or updated data from your app's datastore to Health Connect.\\n- Pull data changes from Health Connect into your app's datastore.\\n- Delete data from Health Connect when it's deleted in your app's datastore.\\n[...]\\nSpecify a`Metadata` object with each`Record`. This includes`clientRecordId`, which is an ID from your app's datastore that you can use to uniquely identify the record. You can use your existing unique key for this. If your data is versioned, also provide a`clientRecordVersion` that aligns with the versioning used in your data. If it's not versioned, you can use the`Long` value of the current timestamp as an alternative.\\n[...]\\nUpsert data to Health Connect using insertRecords. Upserting data means that any existing data in Health Connect gets overwritten as long as the`clientRecordId` values exist in the Health Connect datastore, and the`clientRecordVersion` is higher than the existing value. Otherwise, the upserted data is written as new data.\\n[...]\\nIf your app also reads data from Health Connect, store the Health Connect`id` for records after you upsert them. You need this`id` to process deletions when you pull data changes from Health Connect.\\n[...]\\nThe second part of the syncing process is to pull for any data changes from Health Connect to your app's datastore. The data changes can include updates and deletions.\\n[...]\\nTo get a list of changes to pull from Health Connect, your app needs to keep track of Changes tokens. You can use them when requesting Changes to return both a list of data changes, and a new Changes token to be used next time.\\n[...]\\nTo obtain a Changes token, call getChangesToken and supply the required data types.\\n[...]\\nNow that you've obtained a Changes token, use it to get all Changes. We recommend creating a loop to get through all the Changes where it checks if there are available data changes. Here are the following steps:\\n[...]\\nReflect the changes to your app's datastore. For`UpsertionChange`, use the`id` and the`lastModifiedTime` from its`metadata` to upsert the record. For`DeletionChange`, use the`id` provided to delete the record. This requires that you have stored the record`id` as mentioned in Store Health Connect IDs.\\n[...]\\nTo sync data from a wearable fitness device to Health Connect with low latency, use CompanionDeviceService. This approach works for devices that support BLE GATT Notifications or Indications and target Android 8.0 (API level 26) or higher.`CompanionDeviceService` allows your app to receive data from wearables and write it to Health Connect, even when the app isn't already running. For more details on BLE best practices, see Bluetooth Low Energy overview.\\n[...]\\nFinally, create a class that extends`CompanionDeviceService`. This service handles the connection to the wearable device and receives data through BLE GATT callbacks. When new data is received, it's immediately written to Health Connect.\\n[...]\\nApps can only read data from Health Connect while they are in the foreground. When syncing data from Health Connect, access to Health Connect may be interrupted at any point. For example, your app must handle interruptions midway through a sync when reading a large amount of data from Health Connect, and continue the next time the app is opened.\\n[...]\\nYou can request that your application run in the background and read data from Health Connect. If you request the Background Read permission, your user can grant your app access to read data in the background.\",\n \"position\": 2\n },\n {\n \"url\": \"https://developers.google.com/health/setup\",\n \"title\": \"Set up Google Cloud and OAuth  |  Google Health API  |  Google for Developers\",\n \"description\": \"# Set up Google Cloud and OAuth\\n[...]\\nAccess to the Google Health API is provided through\\nGoogle Cloud. To enable the API and authorize a Google Account, you'll\\nneed a Google Cloud project.\\n[...]\\nWhether you are an existing Fitbit API developer, or new to the Google Health\\nAPI, you'll need to complete this step in order to make calls to the API.\\n[...]\\n## Create a project and an OAuth client\\n[...]\\nUse the Enable the API and get an OAuth 2.0 Client ID button to enable\\nthe Google Health API and get an OAuth 2.0 Client ID:\\n[...]\\n1. If you have an existing Google Cloud project project that you would like to use for the Google Health API, make sure you are logged into the administrator account for that project first. Then select the existing project from the list of available projects after clicking the button. Otherwise, create a new project.\\n2. Select Web Server when it asks \\\"Where are you calling from?\\\".\\n3. Enter https://www.google.com as the value for Authorized redirect\\nURIs. A redirect URI is required to obtain an Authorization Code using OAuth 2.0.\\n4. Once setup is complete, copy the OAuth 2.0 Client ID and Client Secret\\nvalues, and download the Credentials JSON to your local machine.\\n[...]\\nEnable the API and get an OAuth 2.0 Client ID\\n[...]\\nIf you want to manually set up your Google Cloud project, or verify\\nthe setup and retrieve your credentials again:\\n\\n1. Enable Google Health API on the API Enablement page.\\n2. Get an OAuth 2.0 Client ID on the Credentials page.\\n[...]\\nFor more information on setting up OAuth 2.0 using the Google console, see\\nUsing OAuth 2.0 to Access Google APIs.\\n[...]\\n### Add scopes\\n[...]\\nYou must specify the scopes your client is allowed to call on the\\nData Access\\npage:\\n[...]\\n1. On this page, click Add or remove scopes.\\n2. In the API column, search for \\\"Google Health API\\\". Select the scopes you need for your application.\\n3. After selecting all the scopes you need, click Update to return to the Data Access page.\\n4. Click Save.\\n[...]\\nYou have finished setting up your client ID and should now be able to make calls\\nto the Google Health API.\\n[...]\\nThe list of available OAuth2 client libraries\\n[...]\\nto integrate with\\n[...]\\nframeworks\\n[...]\\nTo maintain long-term access to Google APIs without requiring constant\\nuser re-authentication, your application must use a refresh token. For\\ncomprehensive implementation details, including the specific HTTP requests\\nand parameters required, refer to the Google identity platform\\ndocumentation.\\n[...]\\nTo exchange a refresh token for an access token, make an HTTPS POST call to\\nthe Google OAuth 2.0 token endpoint. The following snippet shows an example\\nrequest and response:\\n[...]\\n```\\ncurl -L -X POST 'https://oauth2.googleapis.com/token' \\\\\\n-H 'Content-Type: application/x-www-form-urlencoded' \\\\\\n-d 'client_id=client-id&client_secret=client-secret&refresh_token=refresh-token&grant_type=refresh_token'\",\n \"position\": 3\n },\n {\n \"url\": \"https://developers.google.com/health/libraries\",\n \"title\": \"Client libraries  |  Google Health API  |  Google for Developers\",\n \"description\": \"This page provides client library examples for accessing the Google Health API.\\n[...]\\nThe Google Health API is built on HTTP and JSON, so any standard HTTP client can\\nsend requests to it and parse the responses.\\n[...]\\nHowever, instead of creating HTTP requests and parsing responses manually, you\\nmay want to use the client library examples and downloads featured here.\\n[...]\\nprivate static final String DISCOVERY_URL = \\\"https://health.googleapis.com/$discovery/rest\\\"; // Adjust if needed\\n[...]\\n- `com.google.api.client.*`: Core libraries for Google API client.\\n- `com.google.api.services.health.*`: Generated classes for the Google Health API. (You'll need to generate this based on the API's discovery document).\\n[...]\\n- Configuration:\\n[...]\\n- `CLIENT_SECRETS_PATH`: Path to your `client_secret.json` file.\\n- `TOKENS_DIRECTORY_PATH`: Path to store the tokens.\\n- `API_KEY`: Your API key.\\n- `SCOPES`: The required permissions.\\n- `DISCOVERY_URL`: URL to get the API definition.\\n[...]\\n- `main` Method:\\n[...]\\n- Initializes the Google Health API client and calls `fetchHealthData`.\\n[...]\\n- `createHealthService()`:\\n[...]\\n- Creates an instance of the Google Health API client, setting credentials, app name, and API key.\\n[...]\\n- If no\\n[...]\\n- `fetchHealthData()`:\\n[...]\\n- Makes an API call to the Google Health API (replace the example with your specific method calls).\\n[...]\\n- Prints the response.\\n[...]\\n- Error Handling: The code includes\\n[...]\\n1. Implement OAuth 2.0 Flow:\\n[...]\\n- Use the Google Identity Services library to handle the OAuth flow (result 16.1).\\n[...]\\n- Use the initialized client to make requests to the Google Health API.\\n[...]\\nimport { google } from 'https://apis.google.com/js/api.js';\\nimport { GoogleIdentityServices } from 'https://accounts.google.com/gsi/client';\\n[...]\\nconst CLIENT_ID = 'YOUR_CLIENT_ID';\\nconst API_KEY = 'YOUR_API_KEY';\\nconst DISCOVERY_URL = 'https://health.googleapis.com/$discovery/rest'; // Replace with actual discovery URL if needed\\nconst SCOPES = 'https://www.googleapis.com/auth/health'; // Add other scopes as needed\\n[...]\\nfunction fetchHealthData() {\\n[...]\\n- Import Libraries:\\n[...]\\n- `https://apis.google.com/js/api.js`: Loads the core Google API client.\\n- `https://accounts.google.com/gsi/client`: Loads the Google Identity Services for authentication.\\n[...]\\n- Configuration:\\n[...]\\n- `CLIENT_ID`, `API_KEY`: Replace with your actual credentials.\\n- `DISCOVERY_URL`: The URL to get the API definition. You may need to adjust this based on the final Google Health API setup.\\n- `SCOPES`: Define the necessary permissions your app will need (e.g., to read health data).\\n[...]\\n- `initClient()`:\\n[...]\\n- Loads the Google API client.\\n- Initializes the client with your API key and discovery document.\\n- Initializes the Google Identity Services token client.\\n[...]\\n- `authorize()`:\\n[...]\\n- Checks if a token is already available.\\n- If not, it calls `tokenClient.requestAccessToken()` to start the OAuth flow.\\n[...]\\n- `fetchHealthData()`:\\n[...]\\n- Calls `authorize()` to ensure the user is authenticated.\\n[...]\\n- Makes an API call to the Google Health API (replace the example with your specific calls).\\n[...]\\n- Logs the response.\\n[...]\\n- Error Handling: The code includes basic `try...catch` blocks for error handling.\\n[...]\\n1. Implement OAuth 2.0 Flow:\\n[...]\\n- Use the `google-auth-oauthlib` library to handle the OAuth flow.\\n[...]\\n1. Make API Requests:\\n\\n- Use the initialized client to make requests to the Google Health API.\\n[...]\\n/client_secret.\\n[...]\\n_API_\\n[...]\\nSCOPES = ['https://www.googleapis.com/auth/health'] # Add other scopes as needed\\n[...]\\nDISCOVERY_URL = 'https://health.googleapis.com/$discovery/rest' # Adjust if needed\\n[...]\\ndef create_health_client(creds):\\n[...]\\n\\\"\\\"\\\"Creates a Google Health API client.\\\"\\\"\\\"\\n[...]\\nreturn googleapiclient.discovery.build(\\n'health',\\n'v1', # Replace with the actual API version if needed\\n[...]\\ncredentials=creds,\\ndiscoveryServiceUrl=DISCOVERY_URL,\\n[...]\\ndeveloperKey=API_KEY\\n[...]\\ndef fetch_health_data(client):\",\n \"position\": 4\n },\n {\n \"url\": \"https://developers.google.com/health/get-started\",\n \"title\": \"Get started  |  Google Health API  |  Google for Developers\",\n \"description\": \"This new API leverages Google OAuth, providing a more secure, user-friendly, and\\nscalable solution for accessing and managing health data. Here are some of the\\nbenefits:\\n[...]\\nHow you get started with the Google Health API depends on the type of developer\\nyou are.\\n[...]\\nIf you have no experience with Google APIs or Google Cloud, or need a\\nrefresher, the easiest and fastest\\nway to get started is by going through the codelab. It will show you how to set\\nup a Google Cloud project, an OAuth 2.0 web client, and how to use Visual Studio\\nCode to make your first successful call to the Google Health API.\\n[...]\\nto read the\\n[...]\\nthe Fitbit Web\\n[...]\\nAfter that, either do the codelab, or verify that your Google Cloud setup is\\ncomplete, before you start development with one of our data type guides.\\n[...]\\nComplete the Google Cloud setup\\n[...]\\n- Support : Need assistance? Get access to community forums and our public Issue Tracker on the Support page.\\n- Google Health API Parity Tool : Use this\\ntool to compare endpoints and functionality between the Fitbit Web API and the Google Health API. It also features a context file you can use directly with an LLM, or as part of an Agents.md file in your preferred AI tool.\\n- API reference : Complete REST reference documentation.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_03_0HvtZVUqztaOjRUegznq0399" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://developers.google.com/fit/rest\",\n \"title\": \"REST API | Google Fit\",\n \"description\": \"# REST API\\n\\n Figure 1 : Google Fit REST API.\\n\\nThe Google Fit REST API enables you to store and read health and wellness data in the\\nfitness store from apps on any platform.\\n\\nThe REST API provides resources and methods to:\\n\\n- Create, obtain, list, and modify data sources. A data source represents a unique source of\\nsensor data. All health and wellness data in the fitness store is associated with a particular data source.\\n- Create, obtain, aggregate, and delete datasets. A dataset represents a set of\\ndata points from a particular data source.\\n- List data points and add them to a dataset. A data point represents a sample from a particular\\ndata source.\\n- Create, list, and delete sessions. A session represents a time interval with associated\\nmetadata.\",\n \"position\": 1\n },\n {\n \"url\": \"https://developers.google.com/fit/rest/v1/reference\",\n \"title\": \"API Reference | Google Fit\",\n \"description\": \"API Reference | Google Fit | Google for Developers\\n[...]\\n# API Reference\\n[...]\\nThis API reference organizes information by resource type, with each type having data representations and methods.\\n[...]\\nThe API covers resource types including Users.dataSources, Users.dataSources.dataPointChanges, Users.dataSources.datasets, Users.dataset, and Users.sessions.\\n[...]\\nYou can perform operations like creating, deleting, getting, listing, and updating data sources.\\n[...]\\n| create | `POST  /userId/dataSources` | Creates a new data source that is unique across all data sources belonging to this user. A data source is a unique source of sensor data\\n[...]\\nData sources can\\n[...]\\nraw data coming from hardware sensors\\n[...]\\nan associated data source\\n[...]\\nEach data source produces a unique stream of dataset updates, with a unique data source identifier. Not all changes to data source affect the data stream ID, so that data collected by updated versions of the same application/device can still be considered to belong to the same data source. Data sources are identified using a string generated by the server, based on the contents of the source being created. The`dataStreamId` field should not be set when invoking this method. It will be automatically generated by the server with the correct format. If a`dataStreamId` is set, it must match the format that the server would generate. This format is a combination of some fields from the data source, and has a specific order. If it doesn't match, the request\\n[...]\\n. Specifying\\n[...]\\n| delete | `DELETE\\n[...]\\n/userId/dataSources/\\n[...]\\ndata source. The request will fail if\\n[...]\\ndata source contains any data points.\\n[...]\\n/userId\\n[...]\\n| list | `GET  /userId/dataSources` | Lists all data sources that are visible to the developer, using the OAuth scopes provided. The list is not exhaustive; the user may have private data sources that are only visible to other developers, or calls using other scopes. |\\n[...]\\n| update | `PUT  /userId/dataSources/dataSourceId` | Updates the specified data source. The`dataStreamId`,`dataType`,`type`,`dataStreamName`, and`device` properties with the exception of`version`, cannot be modified. Data sources are identified by their`dataStreamId`. |\\n[...]\\n| Method | HTTP request | Description |\\n| --- | --- | --- |\\n[...]\\n| URIs relative to https://www.googleapis.com/fitness/v1/users, unless otherwise noted |\\n| list | `GET  /userId/dataSources/dataSourceId/dataPointChanges` | Queries for user's data point changes for a particular data source. |\\n[...]\\n/userId/dataSources/dataSourceId\\n[...]\\ntime range specified by\\n[...]\\nFor most data types\\n[...]\\n/userId\\n[...]\\ndatasets/datasetId\\n[...]\\nstart and end times overlap with\\n[...]\\nspecified range of the dataset minimum start time and maximum end time. Specifically, any data point whose start time is less than or equal to the dataset end time and whose end time is greater than or equal to\\n[...]\\ndataset start time. |\\n[...]\\n| patch | `PATCH  /userId/dataSources/dataSourceId/datasets/datasetId` | Adds data points to a dataset. The dataset need not be previously created. All points within the given dataset will be returned with subsquent calls to retrieve this dataset. Data points can belong to more than one dataset. This method does not use patch semantics: the data points provided are merely inserted, with no existing data replaced. |\\n[...]\\n| Method | HTTP request | Description |\\n| --- | --- | --- |\\n| URIs relative to https://www.googleapis.com/fitness/v1/users, unless otherwise noted |\\n| aggregate | `POST  /userId/dataset:aggregate` | Aggregates data of a certain type or stream into buckets divided by a given type of boundary. Multiple data sets of multiple types and from multiple sources can be aggregated into exactly one bucket type per request. |\",\n \"position\": 2\n },\n {\n \"url\": \"https://developers.google.com/fit\",\n \"title\": \"Fit - Google for Developers\",\n \"description\": \"### Connect mind with muscle. Connect with leading apps. Connect with Google Fit.\\n\\nGoogle Fit provides Android and REST APIs to help developers build smarter health and wellness apps. Google Fit APIs can help you discover new insights users want to share with you. Use these insights to build valuable new features to help people train harder, eat healthier, stay calmer, and sleep better. \\n\\n### Connect with leading apps\\n\\nCode less, connect more. You can use the Google Fit APIs to connect with hundreds of other apps while managing a single integration. With user permission, share information with leading health and wellness apps. Learn more \\n\\n### Expand your reach\\n\\nTap into new audiences through wearables. Use the Google Fit APIs to start building Wear OS apps and create experiences for smart watches. Work through our codelab or get started immediately with our app template. Learn more \\n\\n### Build trust\\n\\nSecurity and privacy of health data is at the core of the Google Fit APIs and our robust cloud-based data platform. Benefit from the verification needed to build with Google APIs to show users your app is committed to protecting the information they choose to share with it. Learn more \\n\\n### Help users see the complete the picture\\n\\nUsers need to be able to accurately track their progress, to know when they've hit their goals. By writing data to our platform, your app can be a source of valuable progress data. Help users track their Steps and Heart Point progress using our Goals Client.\\n\\n- Support hardware with better software Build better apps for smart devices with our APIs. Help users see and sync data across devices like smart scales, chest straps, or blood pressure monitors.\\n\\n### Stand out with personalised insights\\n\\nDon't be limited to only what users enter into your app. Learn what your users are tracking to help them guide them to hit their goals faster.\\n\\n- Tap into valuable sensor data Discover sensor data, like heart rate, with our Sensors Client for Android to power innovative, new features. Users can also share other data like their steps, workouts and information calculated from their Google Fit profile (like calories burned) with your app, even when it isn't running.\\n- Motivate users with tailored recommendations Learn about your audience's goals and habits to provide personalised coaching. If you're a food tracking app, discover activity levels to more accurately recommend how many calories to consume. If your app offers mood tracking, discover sleep sessions to show users how sleep habits affect their mood.\\n\\n### Start building with the Google Fit APIs today\\n\\nGet started with Android Get started with REST\",\n \"position\": 3\n },\n {\n \"url\": \"https://developers.google.com/fit/rest/v1/get-started\",\n \"title\": \"Getting Started with the REST API  |  Google Fit  |  Google for Developers\",\n \"description\": \"# Getting Started with the REST API\\n[...]\\nThis tutorial shows you how to activate access to the Fitness REST API, obtain OAuth access\\ntokens, and invoke the API methods using HTTP requests.\\n[...]\\n## Get a Google Account\\n[...]\\nTo use the Fitness REST API, you need a Google Account.\\nIf you already have an account, then you're all set. You may also want to\\ncreate a separate Google Account for testing purposes.\\n[...]\\n## Request an OAuth 2.0 client ID\\n[...]\\nFollow these steps to request an OAuth 2.0 client ID for the Fitness API.\\n[...]\\nAuthorized JavaScript origins , enter the base URL of\\n[...]\\nsite from which requests will originate (for example `https://developers.google.com` is the URL used by the OAuth Playground).\\n[...]\\n8. Under Authorized redirect URI , enter the URL of the site where responses will be handled (for example `https://developers.google.com/oauthplayground` is the URL used by the OAuth Playground).\\n[...]\\nlist\\nof IDs for your project. An OAuth 2.0 Client ID is a string of characters,\\nsomething like this:`780816631155-gbvyo1o7r2pn95qc4ei9d61io4uh48hl.apps.googleusercontent.com`\\n[...]\\n## Try the REST API in the OAuth Playground\\n[...]\\nThe OAuth Playground is the easiest way to familiarize yourself with the\\nFitness REST API by submitting HTTP requests and observing the responses before\\nyou write any client code.\\n[...]\\nTo authorize the Fitness REST API in the OAuth Playground:\\n[...]\\n1. Go to the OAuth Playground.\\n2. Under Step 1 Select & authorize APIs , expand Fitness v1 and select the Fitness scopes to use.\\n[...]\\n3. Click the Authorize APIs button, select the Google API Console project to use, and click Allow when prompted. You will be able to access and modify data associated with the selected Google API Console account.\\n[...]\\n4. Click the Exchange authorization code for tokens button. The OAuth Playground automatically includes this header in the `Authorization:` request header when you submit HTTP requests. Note that the access token will expire after 60 minutes (3600 seconds).\\n[...]\\n### Submit HTTP requests\\n[...]\\nThe following examples demonstrate how to send HTTP requests to list all\\navailable data sources, and to create a new data source. For the Fitness REST\\nAPI, the URI format is:\\n\\n`https://www.googleapis.com/fitness/v1/resourcePath?parameters`\\n[...]\\nTo list all available data sources:\\n[...]\\n1. In HTTP Method , select GET.\\n2. In Request URI , enter `https://www.googleapis.com/fitness/v1/users/me/dataSources`\\n3. Click Send the request.\\n[...]\\nTo create a data source:\\n[...]\\n1. In HTTP Method , select POST.\\n2. In Request URI , enter `https://www.googleapis.com/fitness/v1/users/me/dataSources`\\n3. Click Enter request body.\\n4. In the Request Body window, copy and paste the following JSON:{\\n \\\"dataStreamName\\\": \\\"MyDataSource\\\",\\n \\\"type\\\": \\\"derived\\\",\\n \\\"application\\\": {\\n \\\"detailsUrl\\\": \\\"http://example.com\\\",\\n \\\"name\\\": \\\"Foo Example App\\\",\\n \\\"version\\\": \\\"1\\\"\\n },\\n \\\"dataType\\\": {\\n \\\"field\\\": [\\n {\\n \\\"name\\\": \\\"steps\\\",\\n \\\"format\\\": \\\"integer\\\"\\n }\\n ],\\n \\\"name\\\": \\\"com.google.step_count.delta\\\"\\n },\\n \\\"device\\\": {\\n \\\"manufacturer\\\": \\\"Example Manufacturer\\\",\\n \\\"model\\\": \\\"ExampleTablet\\\",\\n \\\"type\\\": \\\"tablet\\\",\\n \\\"uid\\\": \\\"1000001\\\",\\n \\\"version\\\": \\\"1\\\"\\n }\\n}\\n[...]\\n5. In the Request Body window, click Close.\\n6. Click Send the request.\\n[...]\\nThe request and the response appear on the right side of the page. The request\\nincludes the OAuth access token in the `Authorization` header:\\n[...]\\n`Authorization: Bearer ya29.OAuthTokenValue`\\n[...]\\n## Use cURL to access the Fit REST API\\n[...]\\nYou can use the cURL command line tool to access the\\nFit REST API. You will need an OAuth access token to make requests\\nusing cURL (see the preceding instructions).\\n[...]\\nNote that access tokens expire after an hour. The following example shows a\\nsimple bash script to list all data sources.\\n[...]\\n```\\n#!/bin/bash\\nACCESS_TOKEN=\\\"\\\"\\ncurl \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $ACCESS_TOKEN\\\" \\\\\\n https://www.googleapis.com/fitness/v1/users/me/dataSources\\n\\n```\",\n \"position\": 4\n },\n {\n \"url\": \"https://developers.google.com/fit/rest/v1/running-examples\",\n \"title\": \"Running the Examples  |  Google Fit  |  Google for Developers\",\n \"description\": \"The examples in the following pages show you how to construct HTTP requests to invoke the Fitness\\nREST API:\\n[...]\\n- Working with Sessions\\n- Working with Datasets\\n- Managing Data Sources\\n[...]\\nTo try these examples, you need to obtain an OAuth token first. Then you can submit\\nthe example requests without having to build an application by either:\\n[...]\\n## Submit requests with the OAuth Playground\\n[...]\\nThis process is described in Getting Started. The examples\\nindicate the HTTP method to use and provide the request body.\\n[...]\\n## Submit requests with curl\\n[...]\\nPrerequisites:\\n[...]\\n- Obtain an OAuth token as described in Getting Started.\\n- Install curl if it is not installed on your machine.\\n[...]\\nFore more information about OAuth tokens and authorization, see\\nAuthorizing Requests.\\n[...]\\nTo run each of the examples:\\n[...]\\n1. Run the resulting command on the terminal.\\n2. Edit the command to replace the OAuth token value and the name of the file that contains the request body.\\n3. Copy the `curl` command from the example and paste it into a terminal window.\\n4. Copy and paste the request body from the example into a plain text file.\\n[...]\\n`curl` sends the HTTP request with the authorization header and shows the response on the terminal.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_04_hMalfW1uDhThEbnfEu2k5242" }, { "role": "assistant", "content": "", "reasoning": "Good, I have initial results. Now let me search for Cronometer API and Hevy API, and also health data aggregators, and then extract the actual API doc pages.", "finish_reason": "tool_calls", "reasoning_content": "Good, I have initial results. Now let me search for Cronometer API and Hevy API, and also health data aggregators, and then extract the actual API doc pages.", "tool_calls": [ { "id": "call_00_0AOJKV4n0BaMM0mfbwMP1003", "call_id": "call_00_0AOJKV4n0BaMM0mfbwMP1003", "response_item_id": "fc_00_0AOJKV4n0BaMM0mfbwMP1003", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Cronometer API developer documentation REST\"}" } }, { "id": "call_01_NYEYBZstXCRyzffwlHz36273", "call_id": "call_01_NYEYBZstXCRyzffwlHz36273", "response_item_id": "fc_01_NYEYBZstXCRyzffwlHz36273", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Hevy API documentation developer REST workout tracker\"}" } }, { "id": "call_02_z1iyNiFW3rpnRapT27IR6159", "call_id": "call_02_z1iyNiFW3rpnRapT27IR6159", "response_item_id": "fc_02_z1iyNiFW3rpnRapT27IR6159", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"health data aggregator API Apple Health Google Fit sync service 2024\"}" } }, { "id": "call_03_XRsmmvxHDAhPdoaIj58Y2410", "call_id": "call_03_XRsmmvxHDAhPdoaIj58Y2410", "response_item_id": "fc_03_XRsmmvxHDAhPdoaIj58Y2410", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Google Health Connect cloud backup sync REST API access from server 2024 2025\"}" } } ] }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://pypi.org/project/cronometer-api-mcp/0.1.3/\",\n \"title\": \"cronometer-api-mcp v0.1.3\",\n \"description\": \"MCP server for Cronometer nutrition data using the mobile REST API\\n[...]\\n# cronometer-api-mcp\\n\\n \\n\\nAn MCP (Model Context Protocol) server for Cronometer nutrition tracking, built on the reverse-engineered mobile REST API.\\n[...]\\nUnlike cronometer-mcp, which takes a comprehensive GWT-RPC approach against Cronometer's web backend, this server talks to the same JSON REST API used by the Cronometer Android app -- with clean payloads and stable, versioned endpoints.\\n[...]\\n- **Food log** -- diary entries with food names, amounts, meal groups\\n- **Nutrition data** -- daily macro/micro totals and nutrition scores with per-nutrient confidence\\n- **Food search** -- search the Cronometer food database, get detailed nutrition info\\n- **Diary management** -- add/remove entries, copy days, mark days complete\\n- **Custom foods** -- create foods with custom nutrition data\\n- **Macro targets** -- read weekly schedule and saved templates\\n- **Fasting** -- view history and aggregate statistics\\n[...]\\n## Quick Start\\n[...]\\n### 3. Configure your MCP client\\n[...]\\n## Available Tools\\n[...]\\n### Food Log & Nutrition\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get_food_log` | Diary entries for a date with food names, amounts, and meal groups |\\n| `get_daily_nutrition` | Daily macro and micronutrient totals |\\n| `get_nutrition_scores` | Category scores (Vitamins, Minerals, etc.) with per-nutrient consumed amounts and confidence levels |\\n[...]\\n### Food Search & Details\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `search_foods` | Search the Cronometer food database by name |\\n| `get_food_details` | Full nutrition profile and serving sizes for a food |\\n[...]\\n### Diary Management\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `add_food_entry` | Log a food serving to the diary |\\n| `remove_food_entry` | Remove one or more diary entries |\\n| `add_custom_food` | Create a custom food with specified nutrition |\\n| `copy_day` | Copy all entries from the previous day |\\n| `mark_day_complete` | Mark a diary day as complete or incomplete |\\n[...]\\n### Targets & Tracking\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get_macro_targets` | Weekly macro schedule and saved target templates |\\n| `get_fasting_history` | Fasting history within a date range |\\n| `get_fasting_stats` | Aggregate fasting statistics |\\n[...]\\n## Remote Deployment\\n[...]\\nThe server supports remote deployment with OAuth 2.1 authorization (PKCE) for use with Claude.ai and other remote MCP clients.\\n[...]\\n## How It Works\\n[...]\\nThis server communicates with `mobile.cronometer.com` -- the same REST API used by the Cronometer Android/Flutter app. The API was reverse-engineered through:\\n[...]\\n1. Static analysis of `libapp.so` (Dart AOT snapshot) from the APK to discover endpoint names\\n2. Traffic interception via Frida + mitmproxy to capture exact request/response formats\\n3. Trial-and-error against the live API to confirm payload shapes\\n[...]\\nThe API uses two protocols:\\n[...]\\n- **v2 (`POST /api/v2/*`)** -- JSON-body auth, used for most operations (food search, diary read/write, nutrition, fasting, macros)\\n- **v3 (`DELETE /api/v3/user/{id}/*`)** -- Header-based auth (`x-crono-session`), used for diary entry deletion\\n[...]\\n## Python API\\n[...]\\nYou can use the client directly:\\n[...]\\n```python\\nfrom cronometer_api_mcp.client import CronometerClient\\nfrom datetime import date\\n[...]\\nclient = CronometerClient()\\n[...]\\n# Search for foods\\nresults = client.search_food(\\\"chicken breast\\\")\\n[...]\\n# Get food details\\nfood = client.get_food(results[0][\\\"id\\\"])\\n[...]\\n# Log a serving\\nclient.add_serving(\\n food_id=food[\\\"id\\\"],\\n measure_id=food[\\\"defaultMeasureId\\\"],\\n grams=200,\\n)\\n[...]\\n# Get today's diary\\ndiary = client.get_diary()\\n[...]\\n# Get nutrition scores\\nscores = client.get_nutrition_scores()\\n```\",\n \"position\": 1\n },\n {\n \"url\": \"https://www.sportsfirst.net/sportsapi/cronometer\",\n \"title\": \"Cronometer API Integration for Nutrition Tracking Apps | SportsFirst | SportsFirst\",\n \"description\": \"Website URL: Cronometer API\\n[...]\\nAdditional Resources:\\n[...]\\nCronometer API Documentation: Cronometer Developer Guide\\n[...]\\nCronometer API Support: Visit the Cronometer Support Page for assistance.\",\n \"position\": 2\n },\n {\n \"url\": \"https://pypi.org/project/cronometer-mcp/\",\n \"title\": \"cronometer-mcp v2.0.3\",\n \"description\": \"# cronometer-mcp\\n\\n \\n\\nAn MCP (Model Context Protocol) server that provides access to your Cronometer nutrition data. Pull detailed food logs, daily macro/micro summaries, manage diary entries, fasting, biometrics, and recurring foods — all from Claude, Cursor, or any MCP-compatible client.\\n[...]\\n## Quick Start\\n[...]\\n### 2. Set credentials\\n[...]\\n### 3. Configure your MCP client\\n[...]\\n#### Claude Code (`.mcp.json`)\\n[...]\\n```json\\n{\\n \\\"mcpServers\\\": {\\n \\\"cronometer\\\": {\\n \\\"command\\\": \\\"cronometer-mcp\\\",\\n \\\"env\\\": {\\n \\\"CRONOMETER_USERNAME\\\": \\\"your@email.com\\\",\\n \\\"CRONOMETER_PASSWORD\\\": \\\"your-password\\\"\\n }\\n }\\n }\\n}\\n[...]\\n#### Claude Desktop (`claude_desktop_config.json`)\\n[...]\\n```json\\n{\\n \\\"mcpServers\\\": {\\n \\\"cron\\n[...]\\n\\\": {\\n \\\"command\\\": \\\"cronometer-mcp\\\",\\n \\\"\\n[...]\\n\\\"CRONOMETER_USERNAME\\n[...]\\n\\\"your@email.com\\\",\\n[...]\\nONOMETER_\\n[...]\\ncan also use the full\\n[...]\\n## Available Tools\\n[...]\\n### Food Log & Nutrition\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get_food_log` | Individual food entries with macros + micros for a date range |\\n| `get_daily_nutrition` | Daily macro totals (calories, protein, carbs, fat, fiber) |\\n| `get_micronutrients` | Detailed vitamin/mineral breakdown with period averages |\\n| `export_raw_csv` | Raw CSV export for any data type (servings, exercises, biometrics, etc.) |\\n[...]\\n### Food Search & Diary Management\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `search_foods` | Search the Cronometer food database |\\n| `get_food_details` | Get full nutrition info and serving measure IDs for a food |\\n| `add_food_entry` | Add a food entry to the diary |\\n| `remove_food_entry` | Remove a food entry from the diary |\\n| `copy_day` | Copy all diary entries from one date to another |\\n| `set_day_complete` | Mark a diary day as complete or incomplete |\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n| `get\\n[...]\\nGet daily macro targets\\n[...]\\nor full weekly schedule\\n[...]\\n| `set_\\n[...]\\n| `list\\n[...]\\nList all saved macro\\n[...]\\ntemplates |\\n| `create\\n[...]\\ntemplate |\\n| `set_\\n[...]\\n_schedule` | Assign a template to days of\\n[...]\\nweek as the recurring default |\\n[...]\\n| --- | --- |\\n[...]\\n| Tool | Description |\\n| --- | --- |\\n[...]\\n| `get_recent\\n[...]\\nbiometrics` | Get recently\\n[...]\\n` | Remove a\\n[...]\\n| Tool | Description |\\n| ---\\n[...]\\n| `sync_\\n[...]\\nometer` | Download JSON exports + generate\\n[...]\\n-log.md to disk |\\n[...]\\n## How It Works\\n[...]\\nCronometer does not have a public API for individual users. This server uses the same GWT-RPC (Google Web Toolkit Remote Procedure Call) protocol that the Cronometer web app uses internally:\\n[...]\\n1. Fetches the login page to get an anti-CSRF token\\n2. POSTs credentials to authenticate\\n3. Calls GWT-RPC `authenticate` to get a user ID\\n4. Calls GWT-RPC `generateAuthorizationToken` for short-lived export tokens\\n5. Downloads CSV exports using the token\\n6. Calls GWT-RPC methods directly for diary edits, fasting, biometrics, macro targets, and repeat items\\n[...]\\n## Python API\\n[...]\\nYou can also use the client directly in Python:\\n\\n```python\\nfrom datetime import date, timedelta\\nfrom cronometer_mcp import CronometerClient\\n[...]\\nclient = CronometerClient() # reads from env vars\\n[...]\\n# Get today's food log\\nfoods = client.get_food_log()\\n[...]\\n# Get last 7 days of daily summaries\\nstart = date.today() - timedelta(days=7)\\nsummaries = client.get_daily_summary(start)\\n[...]\\n# Raw CSV export\\ncsv_text = client.export_raw(\\\"exercises\\\", start, date.today())\\n[...]\\n# Copy a day's diary entries\\nclient.copy_day(date(2026, 3, 1), date(2026, 3, 8))\\n[...]\\n# Add a recurring food entry (every weekday)\\nclient.add_repeat_item(\\n food_source_id=12345,\\n measure_id=0, # universal gram-based measure\\n quantity=200,\\n food_name=\\\"Oatmeal\\\",\\n diary_group=1, # Breakfast\\n days_of_week=[1, 2, 3, 4, 5],\\n)\\n[...]\\n# Log a biometric\\nclient.add_biometric(\\\"weight\\\", 218.5, date.today())\\n```\",\n \"position\": 3\n },\n {\n \"url\": \"https://github.com/burke/gocronometer\",\n \"title\": \"burke/gocronometer\",\n \"description\": \"gocronometer is a go module that provides API access to the export methods of Cronometer.com\\n[...]\\n# gocronometer\\n[...]\\ngocronometer is an GPLv2 licensed Go module that provides a client for exporting data from \\nCronometer. It utilizes the export features to retrieve the CSV data from the unpublished API.\\n[...]\\n**NOTE:** This module utilizes the same API the SPA uses. For that reason it should only be used by single users wanting \\nto export their personal data for backup or other reasons. It should never be used for integrations that the enterprise \\nplan would cover. The library is licensed under the GPLv2 to help prevent the unacceptable usage.\\n[...]\\n## Basic Example\\n[...]\\n```go\\n// Create the client.\\nc := gocronometer.NewClient(nil)\\n[...]\\n## Exports Supported\\n[...]\\n| method | description |\\n| --- | --- |\\n| ExportDailyNutrition() | Exports daily nutrition information for the date range provided. |\\n| ExportServings() | Exports servings for the date range provided. |\\n| ExportExercises() | Exports exercises for the date range provided. |\\n| ExportBiometrics() | Exports biometrics for the date range provided. |\\n| ExportNotes( | Exports notes for the date range provided. |\\n[...]\\n## API Magic Values\\n[...]\\nThis library mimics the GWT HTTP requests to perform the export of data. The GWT API exposed by Cronometer is not \\ndesigned to be accessed from anything besides their deployed GWT application. For that reason, there are several values \\nthat can only be obtained from loading the application itself. These values change over time with application updates,\\nand the library must use those new values.\\n[...]\\nThe library includes the values as of the last push of the library. The new values can be provided to the client via\\nthe ClientOptions parameter of the NewClient function.\\n[...]\\n### Magic Values\\n[...]\\n| Name | Location | Changes |\\n| --- | --- | --- |\\n| GWTContentType | Retrieve from request header. | false |\\n| GWTModuleBase | Retrieve from request header. | false |\\n| GWTPermutation | Retrieve from request header. | true |\\n| GWTHeader | Retrieve from GWT request body. | true |\",\n \"position\": 4\n },\n {\n \"url\": \"https://wearipedia.readthedocs.io/en/latest/notebooks/cronometer.html\",\n \"title\": \"Cronometer: Guide to data extraction and analysis — wearipedia documentation\",\n \"description\": \"Cronometer: Guide to data extraction and analysis — wearipedia documentation\\n[...]\\nDo you know that DIET stands for Did I Eat That? Jokes aside, in this notebook we will be doing just that. We will connect to the Cronometer API to analyze the participants nutritional and exercise habits.\\n[...]\\nWe’ve been using the cronometer application for the past few weeks and we will show you how to extract its data, visualize the participants data and compute correlations between multiple metrics. Cronometer does not have a public API, so we would reversed engineered the cornometer api within wearipedia in order to extract servings, daily-nutrition, exercises, notes, and biometrics.\\n[...]\\nIn this guide, we sequentially cover the following nine topics to extract data from Cronometer servers:\\n[...]\\nno OAuth.\\n[...]\\nWe get data via wearipedia in a couple lines of code\\n[...]\\nall of this\\n[...]\\nto file formats compatible by R, Excel\\n[...]\\nand MatLab.\\n[...]\\n1. Setup§\\n[...]\\n## Data Receiver Setup§\\n[...]\\nInstall the`wearipedia` Python package to easily extract data from this app via the Cronometer API.\\n[...]\\n# 2. Authentication/Authorization§\\n[...]\\nTo obtain access to data, authorization is required. All you’ll need to do here is just put in your email and password for your Cronometer account. We’ll use this username and password to extract the data in the sections below.\\n[...]\\n# 3. Data Extraction§\\n[...]\\nData can be extracted via wearipedia, our open-source Python package that unifies dozens of complex wearable device APIs into one simple, common interface.\\n[...]\\nFirst, we’ll set a date range and then extract all of the data within that date range. You can select whether you would like synthetic data or not with the checkbox.\\n[...]\\n```\\n\\n```\\nimport wearipedia\\n\\ndevice = wearipedia.get_device(\\\"cronometer/cronometer\\\")\\n\\nif not synthetic:\\n device.authenticate({\\\"username\\\": email_address, \\\"password\\\": password})\\n\\nparams = {\\\"start_date\\\": start_date, \\\"end_date\\\": end_date}\\n\\ndailySummary = device.get_data(\\\"dailySummary\\\", params=params)\\nservings = device.get_data(\\\"servings\\\", params=params)\\nexercises = device.get_data(\\\"exercises\\\", params=params)\\nbiometrics = device.get_data(\\\"biometrics\\\", params=params)\\n\\n```\\n[...]\\n# 4. Data Exporting§\\n[...]\\nIn this section, we export all of this data to formats compatible with popular scientific computing software (R, Excel, Google Sheets, Matlab). Specifically, we will first export to JSON, which can be read by R and Matlab. Then, we will export to CSV, which can be consumed by Excel, Google Sheets, and every other popular programming language.\\n[...]\\nExporting to JSON is\\n[...]\\n. We export\\n[...]\\ncomplete version that\\n[...]\\nall simultaneously.\\n[...]\\n## Exporting to CSV and XLSX (Excel, Google Sheets, R, Matlab, etc.)§\\n[...]\\nall as separate files.\\n[...]\\n_df = pd.DataFrame.from\\n[...]\\ndf.to\\n[...]\\nThe Cronometer API also gave us access to the participants daily nutrition data. This would enable us to exactly re-create this chart using Python.\\n[...]\\n, let’\\n[...]\\nsee if there\\n[...]\\nBased on the graph, it appears that there is a positive association between\\n[...]\\nin food. To confirm this relationship statistically,\\n[...]\\nwill utilize linear regression to determine the\\n[...]\\nTo perform the linear regression and obtain the correlation coefficient and p-value, you can use statistical functions from the scipy package in Python. The scipy.stats module provides functions for linear regression, correlation coefficient calculation, and p-value calculation.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_00_0AOJKV4n0BaMM0mfbwMP1003" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://api.hevyapp.com/docs/\",\n \"title\": \"Swagger UI - Hevy\",\n \"description\": \"Swagger UI\\n\\nExplore\\n\\n```\\n 0.0.1 \\n```\\n\\n```\\nOAS 3.0\\n```\\n\\n## Hevy API Docs\\n\\n```\\n Welcome to Hevy's public API! We're just starting to roll this out and depending on your\\n feedback, we'll be adding more features and endpoints. Also, we make no guarantees that \\n we won't completely change the structure or abandon the project entirely so use it at\\n your own risk. Currently, this API is only available to Hevy Pro users. You can get your \\n key on our web app at https://hevy.com/settings?developer. If you have any questions,\\n please reach out to pedro@hevyapp.com 🤝.\\n\\n```\\n\\n### Workouts\\n\\nGET\\n\\n/v1/workouts\\n\\nGet a paginated list of workouts\\n\\nPOST\\n\\n/v1/workouts\\n\\nCreate a new workout\\n\\nGET\\n\\n/v1/workouts/count\\n\\nGet the total number of workouts on the account\\n\\nGET\\n\\n/v1/workouts/events\\n\\nRetrieve a paged list of workout events (updates or deletes) since a given date. Events are ordered from newest to oldest. The intention is to allow clients to keep their local cache of workouts up to date without having to fetch the entire list of workouts.\\n\\nGET\\n\\n/v1/workouts/{workoutId}\\n\\nGet a single workout’s complete details by the workoutId\\n\\nPUT\\n\\n/v1/workouts/{workoutId}\\n\\nUpdate an existing workout\\n\\n### Users\\n\\nGET\\n\\n/v1/user/info\\n\\nGet user info\\n\\n### Routines\\n\\nGET\\n\\n/v1/routines\\n\\nGet a paginated list of routines\\n\\nPOST\\n\\n/v1/routines\\n\\nCreate a new routine\\n\\nGET\\n\\n/v1/routines/{routineId}\\n\\nGet a routine by its Id\\n\\nPUT\\n\\n/v1/routines/{routineId}\\n\\nUpdate an existing routine\\n\\n### ExerciseTemplates\\n\\nGET\\n\\n/v1/exercise_templates\\n\\nGet a paginated list of exercise templates available on the account.\\n\\nPOST\\n\\n/v1/exercise_templates\\n\\nCreate a new custom exercise template.\\n\\nGET\\n\\n/v1/exercise_templates/{exerciseTemplateId}\\n\\nGet a single exercise template by id.\\n\\n### RoutineFolders\\n\\nGET\\n\\n/v1/routine_folders\\n\\nGet a paginated list of routine folders available on the account.\\n\\nPOST\\n\\n/v1/routine_folders\\n\\nCreate a new routine folder. The folder will be created at index 0, and all other folders will have their indexes incremented.\\n\\nGET\\n\\n/v1/routine_folders/{folderId}\\n\\nGet a single routine folder by id.\\n\\n### ExerciseHistory\\n\\nGET\\n\\n/v1/exercise_history/{exerciseTemplateId}\\n\\nGet exercise history for a specific exercise template\\n\\n### Measurements\\n\\nGET\\n\\n/v1/body_measurements\\n\\nGet a paginated list of body measurements for the authenticated user\\n\\nPOST\\n\\n/v1/body_measurements\\n\\nCreate a body measurement entry for a given date. Returns 409 if an entry already exists for that date.\\n\\nGET\\n\\n/v1/body_measurements/{date}\\n\\nGet a single body measurement by date\\n\\nPUT\\n\\n/v1/body_measurements/{date}\\n\\nUpdate an existing body measurement entry for a given date. All fields are overwritten; omitted fields are set to null.\\n\\n#### Schemas\\n\\nPostWorkoutsRequestSet\\n\\nPostWorkoutsRequestExercise\\n\\nPostWorkoutsRequestBody\\n\\nPostRoutinesRequestSet\\n\\nPostRoutinesRequestExercise\\n\\nPostRoutinesRequestBody\\n\\nPutRoutinesRequestSet\\n\\nPutRoutinesRequestExercise\\n\\nPutRoutinesRequestBody\\n\\nPostRoutineFolderRequestBody\\n\\nBodyMeasurement\\n\\nPutBodyMeasurement\\n\\nSet\\n\\nExercise\\n\\nExerciseHistoryEntry\\n\\nCustomExerciseType\\n\\nMuscleGroup\\n\\nEquipmentCategory\\n\\nExerciseTemplate\\n\\nCreateCustomExerciseRequestBody\\n\\nRoutineFolder\\n\\nRoutine\\n\\nUserInfo\\n\\nUserInfoResponse\\n\\nWorkout\\n\\nUpdatedWorkout\\n\\nDeletedWorkout\\n\\nPaginatedWorkoutEvents\",\n \"position\": 1\n },\n {\n \"url\": \"https://github.com/Klivess/HevySharp/blob/master/DOCUMENTATION.md\",\n \"title\": \"DOCUMENTATION.md at master · Klivess/HevySharp\",\n \"description\": \"```md\\n# HevySharp — Full API Reference\\n[...]\\nComplete reference for every class, method, and model in the HevySharp library.\\n[...]\\n- HevyAPI Client\\n - Constructors\\n -\\n[...]\\n- User\\n - Workouts\\n - Routines\\n - Routine Folders\\n - Exercise Templates\\n - Exercise History\\n[...]\\n## HevyAPI Client\\n[...]\\n**Namespace:** `HevySharp`\\n[...]\\nThe main entry point for interacting with the Hevy API.\\n[...]\\nkey by calling `GET /v1/user/info`. On success, sets `\\n[...]\\nAuthorised = true` and attaches the key to all subsequent requests.\\n[...]\\n### Workouts\\n[...]\\n#### `GetWorkouts`\\n[...]\\n```csharp\\npublic async Task GetWorkouts(int page = 1, int pageSize = 5)\\n```\\n[...]\\nGets a paginated list of workouts ordered newest to oldest.\\n[...]\\n| Parameter | Type | Default | Description |\\n[...]\\n|---|---|---|---|\\n[...]\\n| `page\\n[...]\\n-based) |\\n[...]\\n| `pageSize\\n[...]\\n| `5\\n[...]\\npage (max\\n[...]\\n0) |\\n[...]\\n**API endpoint:** `GET /v1/workouts?page={page}&pageSize={pageSize}`\\n[...]\\n**Returns:** `PaginatedWorkoutResponse` containing `Page`, `PageCount`, and `Workouts` list.\\n[...]\\n#### `GetWorkout`\\n[...]\\n```csharp\\npublic async Task GetWorkout(string workoutId)\\n```\\n[...]\\nGets a single workout by ID with all exercises and sets.\\n[...]\\n**API endpoint:** `GET /v1/workouts/{workoutId}`\\n[...]\\n#### `CreateWorkout`\\n[...]\\n```csharp\\npublic async Task CreateWorkout(HevyWorkout workout)\\n```\\n[...]\\nworkout. The library automatically:\\n[...]\\n**API endpoint:** `POST /v1/workouts`\\n[...]\\n**Returns:** The created `HevyWorkout` (with server-assigned `Id`).\\n[...]\\n#### `UpdateWorkout`\\n[...]\\n```csharp\\npublic async Task UpdateWorkout(string workoutId, HevyWorkout workout)\\n```\\n[...]\\nUpdates an existing workout. The library automatically:\\n[...]\\n**API endpoint:** `PUT /v1/workouts/{workoutId}`\\n[...]\\n#### `GetWorkoutCount`\\n[...]\\n**API endpoint:** `GET /v1/workouts/count`\\n[...]\\n**Returns:** `int` — the workout count.\\n[...]\\n#### `GetWorkoutEvents`\\n[...]\\n```csharp\\npublic async Task GetWorkoutEvents(int page =\\n[...]\\n1, int pageSize =\\n[...]\\n**API endpoint:** `GET /v1/workouts/events?page={page}&pageSize={pageSize}`\\n[...]\\ninatedWorkoutEventResponse`\\n[...]\\n### Routines\\n[...]\\n#### `CreateRoutine\\n[...]\\n### Exercise Templates\\n[...]\\n### Exercise History\\n[...]\\n## Models (Schemas)\\n[...]\\n### HevyWorkout\\n[...]\\n|---|---|---|---|\\n[...]\\n### HevyExercise\\n[...]\\n| Property | Type |\\n[...]\\nKey | Description |\\n|---|---|---|---|\\n[...]\\n?` |\\n[...]\\nexercise_template_\\n[...]\\n) |\\n[...]\\nSupersetId\\n[...]\\n?` |\\n[...]\\n### HevyWorkoutEvent\\n[...]\\n## Paginated Responses\\n[...]\\nAll list endpoints return paginated responses. Each shares a common structure:\\n[...]\\n### PaginatedWorkoutResponse\\n[...]\\n### PaginatedRoutineResponse\\n[...]\\n### PaginatedRoutine\\n[...]\\n### Paginated\\n[...]\\n### PaginatedWorkoutEventResponse\\n[...]\\n### WorkoutCountResponse\\n[...]\\n## Automatic Behaviours\\n[...]\\nThe Hevy API requires POST and PUT bodies to be wrapped in their resource name. HevySharp does this automatically:\\n[...]\\n| Method | JSON Wrapper Key |\\n|---|---|\\n| `CreateWorkout` / `UpdateWorkout` | `\\\"workout\\\"` |\\n| `CreateRoutine` / `UpdateRoutine` | `\\\"routine\\\"` |\\n| `CreateRoutineFolder` | `\\\"routine_folder\\\"` |\\n| `CreateExerciseTemplate` | `\\\"exercise_template\\\"` |\\n[...]\\n## Testing and Dependency Injection\",\n \"position\": 2\n },\n {\n \"url\": \"https://github.com/dmzoneill/hevyapp-api\",\n \"title\": \"dmzoneill/hevyapp-api\",\n \"description\": \"# Repository: dmzoneill/hevyapp-api\\n[...]\\n# hevy-api\\n[...]\\n- Samples\\n- Python pyplot example\\n- Chart js example\\n[...]\\n## Overviews\\n[...]\\n- login.md\\n- account.md\\n- workoutcount.md\\n- feed_workouts_paged.md\\n- routines_sync_batched.md\\n- user_preferences.md\\n[...]\\n## How to dissect https calls for yourself\\n[...]\\nHevy should use the proxy with the previously\\n[...]\\ncertificate and in charles you can now see the decrypted https requests.\",\n \"position\": 3\n },\n {\n \"url\": \"https://skills.rest/skill/hevy\",\n \"title\": \"hevy: Access Hevy workouts via public API | skills.rest\",\n \"description\": \"hevy: Access Hevy workouts via public API | skills.rest\\n[...]\\nAccess Hevy workouts via public API.\\n[...]\\n## System Documentation\\n[...]\\nThe Hevy public API enables programmatic access to workout data, allowing automation and integration with your tools and dashboards.\\n[...]\\n- List workouts, fetch workout details, and retrieve exercise history via the /v1/workouts endpoints.\\n- Create and update workouts programmatically, enabling automation of workout logging and analysis.\\n- Use cases include syncing workouts to dashboards, mobile apps, or home automation workflows.\\n[...]\\nLoad HEVY_API_KEY from your environment (.env) and set the base URL to https://api.hevyapp.com. Then make authenticated requests, for example: curl -H \\\"api-key: $HEVY_API_KEY\\\" \\\"https://api.hevyapp.com/v1/workouts?page=1&pageSize=5\\\"\",\n \"position\": 4\n },\n {\n \"url\": \"https://github.com/dmzoneill/hevyapp-api/tree/main/api\",\n \"title\": \"hevyapp-api/api at main · dmzoneill/hevyapp-api · GitHub\",\n \"description\": \"hevyapp-api/api at main · dmzoneill/hevyapp-api · GitHub\\n[...]\\n# api\\n[...]\\naccount.md\\n\\naccount.md\\n[...]\\nfeed_workouts_paged.md\\n\\nfeed_workouts_paged.md\\n[...]\\nlogin.md\\n\\nlogin.md\\n[...]\\nnew-routine.md\\n\\nnew-routine.md\\n[...]\\nroutines_sync_batch.md\\n\\nroutines_sync_batch.md\\n[...]\\nupdate-routine.md\\n\\nupdate-routine.md\\n[...]\\nuser_preferences.md\\n[...]\\nuser_preferences.md\\n[...]\\nworkoutcount.md\\n[...]\\nworkoutcount.md\\n[...]\\nworkouts_batch.md\\n\\nworkouts_batch.md\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_01_NYEYBZstXCRyzffwlHz36273" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://pulshealth.com/sync/\",\n \"title\": \"PulsHealth - Wearable Health Data for AI\",\n \"description\": \"# PulsHealthSync\\n[...]\\nReal-time collection and sync of wearable health data. A package that manages encryption, consent, and the quirks of each wearable platform — fully managed or self-hosted.\\n[...]\\nBuilding a reliable sync pipeline that handles encryption, consent, and the quirks of each wearable platform is a significant engineering effort. PulsHealthSync handles it.\\n[...]\\nMulti-Source Aggregation\\n[...]\\nConnect and aggregate health data from Apple Health, Google Fit, Fitbit, Garmin, and more into a unified, normalized format.\\n[...]\\nReal-Time Sync\\n[...]\\nContinuous synchronization keeps wearable data up-to-date across all connected sources. Query the most recent workout, ECG, or sleep stages as they happen.\\n[...]\\nFully Managed or Self-Hosted\\n[...]\\nUse PulsHealth's hosted database for an end-to-end solution, or point the package at your own endpoint — the data flows to your storage, your way.\\n[...]\\nEnd-to-end encryption in transit and at rest. Granular user consent controls that can be changed at any time.\\n[...]\\nImport years of historical health data from supported platforms with a single connection.\\n[...]\\nPair PulsHealthSync with the AI Health Agent for on-device or cloud-based use. The agent reads from synced data across multiple wearable sources.\\n[...]\\nPower your health app with unified data from all major wearables and health platforms, kept current with real-time sync.\",\n \"position\": 1\n },\n {\n \"url\": \"https://docs.median.co/docs/health-bridge\",\n \"title\": \"Health Bridge\",\n \"description\": \"Build Smarter Wellness Features with Health Bridge for Apple HealthKit and Google Health Connect\\n[...]\\nHealth Bridge provides a unified interface to access and sync health data from users' devices using Apple HealthKit (iOS) and Google Health Connect (Android). The plugin enables you to fetch health metrics such as steps, heart rate, calories, and sleep data - allowing you to build powerful wellness and fitness features in your app.\\n[...]\\nHealth Bridge takes care of handling platform-specific details like permissions, data sources, and user consent, so you can focus on delivering value to your users. The plugin abstracts away the complexity of working with different health platforms while maintaining full access to rich health data.\\n[...]\\n- Unified Interface: Single API that works seamlessly across iOS (Apple HealthKit) and Android (Google Health Connect)\\n- Platform Handling: Automatically manages platform-specific permissions, data sources, and user consent flows\\n- Wellness Features: Access comprehensive health metrics including steps, heart rate, calories, sleep, and more\\n- Data Accessibility: Retrieve historical health data with flexible date ranges and grouping options\\n[...]\\nPlatform Permissions Model: Permissions work differently on each platform:\\n[...]\\n- Android: Returns a list of granted and declined data types when requesting permissions\\n- iOS: Does not return any information about permission status. The OS will prompt the user when data is first requested, and you won't get confirmation about which permissions were granted\\n[...]\\nAlthough not required, we recommend calling `requestPermissions()` upfront as it improves user transparency and experience. This prompts users to grant access to the specific health data types your app will use.\\n[...]\\nThis method accepts an array of data types and returns an object indicating which permissions were granted or declined.\\n[...]\\nReturns a list\\n[...]\\nDoes not return\\n[...]\\nwill prompt the\\n[...]\\nYou can optionally skip requestPermissions() and directly call getData() (next step) and the OS will handle permissions automatically.\\n[...]\\nAfter permissions are granted (or requested implicitly), use the `getData()` method to retrieve health data. You can define the following parameters:\\n[...]\\n- The specific `dataTypes` to fetch (from the supported list)\\n- A `startDate` and `endDate` in ISO 8601 format\\n- An optional `bucket` to group data (e.g., by day or hour)\\n[...]\\n| Parameter | Type | Required | Description |\\n| --- | --- | --- | --- |\\n| `dataTypes` | `Array` | Yes | The specific data types to fetch (from the supported list) |\\n| `startDate` | `string` | Yes | Start date in ISO 8601 format |\\n| `endDate` | `string` | Yes | End date in ISO 8601 format |\\n| `bucket` | `string` | No | Optional grouping for data (default: 'raw') |\\n[...]\\nBucket Options:\\n[...]\\n| Bucket | Description |\\n| --- | --- |\\n| `raw` | Raw, ungrouped data points |\\n| `minute` | Data grouped per minute |\\n| `hour` | Data grouped per hour |\\n| `day` | Data grouped per day (recommended) |\\n[...]\\n```javascript\\nconst result = await median.healthBridge.getData({\\n dataTypes: granted, // list of granted permissions from previous step\\n startDate: '2025-05-01T00:00:00Z',\\n endDate: '2025-05-08T00:00:00Z',\\n bucket: 'day'\\n});\\n[...]\\n(result.\\n[...]\\nWant to show a daily step chart for the past week? Just fetch steps with bucket: 'day' and map the values to your chart component.\\n[...]\\nDue to callouts to Apple services, the Health Bridge integration cannot be tested in the App Studio virtual simulator. Instead, any integration tests must be run on a physical device or on Xcode or Android Studio simulators.\\n[...]\\nAfter adding test data to your account, follow the steps below to access the data through the Health Bridge:\\n[...]\\n| Step 1 | Step 2 | Step 3 |\\n| --- | --- | --- |\\n| | | |\\n| Select the data points, bucket and date range for the request | Confirm the access | Access the returned data in the JSON object |\",\n \"position\": 2\n },\n {\n \"url\": \"https://docs.gethealthie.com/reference/2024-11-01/objects/googlefit\",\n \"title\": \"GoogleFit | Healthie API Docs\",\n \"description\": \"GoogleFit | Healthie API Docs Skip\\n[...]\\n# GoogleFit\\n[...]\\nA GoogleFit Sync\\n[...]\\n`id`· ID!· required · The unique identifier of the Google fit\\n[...]\\n`last_sync_date`· ISO8601DateTime· The last time the apple health was synced\\n[...]\\n```\\n\\\"\\\"\\\"A GoogleFit Sync\\\"\\\"\\\"type GoogleFit { \\\"\\\"\\\" The unique identifier of the Google fit \\\"\\\"\\\" id: ID! \\\"\\\"\\\" The last time the apple health was synced \\\"\\\"\\\" last_sync_date: ISO8601DateTime}\\n```\",\n \"position\": 3\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/health-connect/comparison-guide\",\n \"title\": \"Health Connect comparison guide  |  Android health & fitness  |  Android Developers\",\n \"description\": \",\\nusers often need to switch between platforms to manage their\\n[...]\\n. Health\\nConnect solves this by providing a single place for Android users to manage\\naccess to their health and fitness data, offering granular control.\\n[...]\\nThe Google Health API platform offers two primary integration paths: Health\\nConnect for on-device Android data, and the Google Health API for cloud-based,\\ncross-platform data.\\n[...]\\n| API | Status | Audience | Storage |\\n| --- | --- | --- | --- |\\n| Health Connect | Available | Android mobile developers | On-device |\\n| Google Health API | Available | Web, server-to-server (S2S), and platform-agnostic developers | Cloud |\\n| Fitbit Web API | Transitioning | Existing Fitbit ecosystem developers | Cloud |\\n| Google Fit API | Deprecating | Legacy Google Fit (Android and REST) API developers | Cloud |\\n[...]\\nWe don't recommend migrating to Health Connect if you're an existing Google\\nFitbit Web API developer. However, if you're integrated with the Fit APIs, we\\nrecommend migrating to Health Connect only if you are a step-tracking app.\\n[...]\\n> [!NOTE]\\n> Note: The Google Fit APIs have been deprecated and we plan to support them until 2026 . See Migration guide for instructions on migrating to Health Connect.\\n[...]\\nHealth Connect unifies data across Android's portfolio of devices and apps into\\nan ecosystem, providing a common health platform for Android developers. It\\nprovides a secure, on-device store for health and fitness data, standardizes\\nthe data schema, and centralizes permissions control.\\n[...]\\n- Architecture: Local / Android Path (Mobile-centric).\\n- Availability: Part of the Android framework starting with Android 14. For Android 13 and lower, it is available through the Google Play Store.\\n- Data storage: Device-centric, where data is stored locally on the user's device.\\n[...]\\n- Intended audience: Health Connect is intended for Android mobile developers.\\n- Device-centric: Users access and store data on their devices.\\n- No account needed: The data is not associated with a Google Account.\\n- Built-in permissions: Health and fitness data management is centralized.\\n[...]\\nThe Google Health API is a unified web\\nAPI designed for server-to-server (S2S) interactions. It is an\\naccount-centric, platform-agnostic interface that\\nreplaces the existing Fitbit Web API functionality.\\n[...]\\n- Architecture: Cloud Path (Server-to-server).\\n- Audience: Developers requiring a reconciled view of health and medical data across platforms.\\n- Data needs: Required if your app is web-based, uses the OAuth protocol, or requires low-latency data from Fitbit or Pixel Watch.\\n- Availability: Available.\\n[...]\\nThe following APIs are considered legacy and are being deprecated or\\ntransitioned to newer alternatives.\\n[...]\\nThe Google Fit API (including the REST API) is officially scheduled\\nfor end of service by the end of 2026. We recommend integrating with\\nHealth Connect or the Google Health API. All developers using Google Fit APIs\\nmust transition. We recommend removing Google Fit integration and encouraging\\nusers to connect to new integrations. For instructions, see the\\nFit migration guide.\\n[...]\\nThe Fitbit Web API is a platform-agnostic interface to integrate\\nwith the Fitbit ecosystem. In the Fitbit Web API, the user's data is tied to\\ntheir Fitbit account instead of their device. Existing developers should\\nprepare to transition to the Google Health API to access unified health data.\\n[...]\\n> [!CAUTION]\\n> Caution: The Fitbit Web API will migrate to the Google Health API. For instructions, see the Fitbit migration guide.\",\n \"position\": 4\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/health-connect\",\n \"title\": \"Health Connect  |  Android health & fitness  |  Android Developers\",\n \"description\": \"### Health Connect: simplify connectivity between apps\\n[...]\\nHealth and fitness apps record valuable data, including medical records. With permission from your users, you can unlock the full potential of this data by combining it to generate powerful insights.\\n[...]\\nHealth Connect stores and structures health and fitness data. It also accounts for how different data types are measured. These data types include heart rate measurements taken immediately, step count taken over time, and sleep data taken in sessions.\\n[...]\\nThe Medical Records feature extends Health Connect to include basic medical data in the Fast Healthcare Interoperability Resources (FHIR®) format. It provides APIs for applications to read and write medical data, along with a user interface for browsing the data and managing permissions.\\n[...]\\n### CRUD operations on record and data synchronization\\n[...]\\nThe platform provides standard insert, update, and delete functions for recorded data. Health Connect also includes functionality that allows client apps to synchronize data out of Health Connect.\\n[...]\\nHealth Connect is compatible with Android SDK version 28 (Pie) and higher. The SDK allows client apps to determine whether the Health Connect API is on the user's Android-powered device. If it isn't, Health Connect triggers an availability check to determine whether the user's device is compatible.\\n[...]\\n### Reading with Health Connect\\n[...]\\nEnable applications to continuously access a user's health data, even when the app is running in the background. This ensures uninterrupted access for analysis, synchronization, and utilization, offering a seamless health tracking experience.\\n[...]\\n### Introducing new APIs for health and fitness in Health Connect by Android\\n[...]\\nLearn about the new Health Connect APIs.\\n[...]\\n### Unlock deeper health insights: Health Connect Jetpack SDK is now in beta and new feature updates\\n[...]\\nWe're excited to announce significant Health Connect updates like the Jetpack SDK Beta, new datatypes and new permissions that will enable richer, more insightful app functionalities.\\n[...]\\n## Health Connect Jetpack Library 1.1.0 is now stable\\n[...]\\nWe are excited to announce that the Health Connect Jetpack library has reached its 1.1.0 stable release. This milestone provides developers with the confidence and reliability needed to build production-ready health and fitness experiences at scale.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_02_z1iyNiFW3rpnRapT27IR6159" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://support.google.com/android/answer/15323271?hl=en\",\n \"title\": \"Back up & restore your Health Connect data - Android Help\",\n \"description\": \"Back up & restore your Health Connect data - Android Help\\n\\n# Back up & restore your Health Connect data\\n\\nRegularly back up your Health Connect data to safeguard your health, fitness, and medical journey. If you lose or damage your device, you can restore your valuable information easily.\\n\\nImportant: To move your Health Connect data when switching phones with a cable, you can use device-to-device transfer. Learn more about device to device transfer.\\n\\n## Export & import your Health Connect data\\n\\nYou can easily export your Health Connect data to a cloud storage provider and import it in Health Connect on your other device. This helps you keep your data safe. Important: Export and import of health records isn’t supported at this time.\\n\\n## What you need\\n\\nTo use this feature, you need an Android device with version 14 and up.\\n\\n## Export your Health Connect data\\n\\nYou can set a periodical data export. Your Health Connect data is bundled in a zip file and saved to a cloud storage provider of your choice. You can schedule these exports on a daily, weekly, or monthly basis.\\n\\nTurn Scheduled export on or off.\\n\\n- Select a frequency between daily, weekly, or monthly exports.\\n\\n### Save to a cloud provider\\n\\nFrom a list of cloud storage apps already installed on your device, select where you want to save your data.\\n\\n- If you don’t have a cloud storage app, download one from Google Play.\\n\\nSelect a location in the app.\\n\\n- By default, the file is named “Health Connect.zip.” You can rename it if you want.\\n\\nTip: After a successful export, you can find the file name, app where it was exported to and the date on which the file was exported.\\n\\n### Turn Scheduled export on or off\\n\\n1. Tap Save.\\n2. Open your device's Settings app.\\n3. In the search bar, search`Health Connect`.\\n4. Tap Manage data Backup and restore Scheduled export.\\n5. Turn Scheduled export on or off.\\n\\nTip: If you turn off “Scheduled export,” it won’t delete your previously exported data automatically.\\n\\n## Import your Health Connect data\\n\\nSelect the Health Connect data file you want to import.\\n\\n- By default, the file is named “Health Connect.zip.”\\n- If you’ve changed the file name during export, find the file with the updated file name.\\n\\n## Delete your exported data\\n\\nYou can delete the data you previously exported from Health Connect.\\n\\nTo delete, find the file by the default name “Health Connect.zip.”\\n\\n- If you’ve changed the file name during export, find the file with the updated file name.\\n\\n## Related resources\\n\\n- Find your Health Connect data\\n- Manage your Health Connect data\\n- Delete your data from Health Connect\\n\\n## Was this helpful?\\n\\nHow can we improve it?\\n\\nYesNo\\n\\nSubmit\\n\\n## Need more help?\\n\\n### Try these next steps:\\n\\nPost to the help community Get answers from community members\\n\\ntrue\\n\\nSearch\\n\\nClear search\\n\\nClose search\\n\\nGoogle apps\\n\\nMain menu\\n\\n9781866461548157246\\n\\ntrue\\n\\nSearch Help Center\\n\\nfalse\\n\\ntrue\\n\\ntrue\\n\\ntrue\\n\\nfalse\\n\\nfalse\\n\\nfalse\\n\\nfalse\",\n \"position\": 1\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/health-connect/comparison-guide\",\n \"title\": \"Health Connect comparison guide  |  Android health & fitness  |  Android Developers\",\n \"description\": \"The Google Health API platform offers two primary integration paths: Health\\nConnect for on-device Android data, and the Google Health API for cloud-based,\\ncross-platform data.\\n[...]\\n| API | Status | Audience | Storage |\\n| --- | --- | --- | --- |\\n| Health Connect | Available | Android mobile developers | On-device |\\n| Google Health API | Available | Web, server-to-server (S2S), and platform-agnostic developers | Cloud |\\n| Fitbit Web API | Transitioning | Existing Fitbit ecosystem developers | Cloud |\\n| Google Fit API | Deprecating | Legacy Google Fit (Android and REST) API developers | Cloud |\\n[...]\\n3 and lower,\\n[...]\\nis available through the Google Play Store.\\n- Data storage: Device-centric\\n[...]\\ns device.\\n[...]\\nThe Google Health API is a unified web\\nAPI designed for server-to-server (S2S) interactions. It is an\\naccount-centric, platform-agnostic interface that\\nreplaces the existing Fitbit Web API functionality.\\n[...]\\n- Architecture: Cloud Path (Server-to-server).\\n- Audience: Developers requiring a reconciled view of health and medical data across platforms.\\n- Data needs: Required if your app is web-based, uses the OAuth protocol, or requires low-latency data from Fitbit or Pixel Watch.\\n- Availability: Available.\\n[...]\\nThe Google Fit API (including the REST API) is officially scheduled\\nfor end of service by the end of 2026. We recommend integrating with\\nHealth Connect or the Google Health API. All developers using Google Fit APIs\\nmust transition. We recommend removing Google Fit integration and encouraging\\nusers to connect to new integrations. For instructions, see the\\nFit migration guide.\\n[...]\\nThe Fitbit Web API is a platform-agnostic interface to integrate\\nwith the Fitbit ecosystem. In the Fitbit Web API, the user's data is tied to\\ntheir Fitbit account instead of their device. Existing developers should\\nprepare to transition to the Google Health API to access unified health data.\\n[...]\\n> [!CAUTION]\\n> Caution: The Fitbit Web API will migrate to the Google Health API. For instructions, see the Fitbit migration guide.\",\n \"position\": 2\n },\n {\n \"url\": \"https://android-dot-devsite-v2-prod.appspot.com/health-and-fitness/health-connect/sync-data\",\n \"title\": \"Synchronize data  |  Android health & fitness  |  Android Developers\",\n \"description\": \"This guide is compatible with Health Connect version 1.1.0-alpha12.\\n[...]\\nMost apps that integrate with Health Connect have their own datastore that serves as the source of truth. Health Connect provides ways to keep your app in sync.\\n[...]\\n- Feed new or updated data from your app's datastore to Health Connect.\\n- Pull data changes from Health Connect into your app's datastore.\\n- Delete data from Health Connect when it's deleted in your app's datastore.\\n[...]\\nincludes`clientRecordId`, which is an ID from your app'\\n[...]\\nyou can use to uniquely identify the record. You can use your\\n[...]\\n. If your data\\n[...]\\nversioned, also provide a\\n[...]\\nclientRecordVersion`\\n[...]\\naligns with the\\n[...]\\nused in your data. If it's not versioned, you can use the`Long` value of the current timestamp\\n[...]\\nan alternative.\\n[...]\\nUpsert data to Health Connect using insertRecords. Upserting data means that any existing data in Health Connect gets overwritten as long as the`clientRecordId` values exist in the Health Connect datastore, and the`clientRecordVersion` is higher than the existing value. Otherwise, the upserted data is written as new data.\\n[...]\\nIf your app also reads data from Health Connect, store the Health Connect`id` for records after you upsert them. You need this`id` to process deletions when you pull data changes from Health Connect.\\n[...]\\nThe second part of the syncing process is to pull for any data changes from Health Connect to your app's datastore. The data changes can include updates and deletions.\\n[...]\\nTo get a list of changes to pull from Health Connect, your app needs to keep track of Changes tokens. You can use them when requesting Changes to return both a list of data changes, and a new Changes token to be used next time.\\n[...]\\nTo obtain a Changes token, call getChangesToken and supply the required data types.\\n[...]\\nNow that you've\\n[...]\\na Changes token, use it to\\n[...]\\nChanges. We recommend creating a\\n[...]\\nthe Changes where it checks if there\\n[...]\\n. Here are the following\\n[...]\\nReflect the changes to your app's datastore. For`UpsertionChange`, use the`id` and the`lastModifiedTime` from its`metadata` to upsert the record. For`DeletionChange`, use the`id` provided to delete the record. This requires that you have stored the record`id` as mentioned in Store Health Connect IDs.\\n[...]\\nyour app, make sure\\n[...]\\nUse deleteRecords\\n[...]\\nclientRecordId\\n[...]\\nconvenient to batch\\n[...]\\ndeletion. An alternative deleteRecords\\n[...]\\ntimeRangeFilter` is\\n[...]\\nTo sync data from a wearable fitness device to Health Connect with low latency, use CompanionDeviceService. This approach works for devices that support BLE GATT Notifications or Indications and target Android 8.0 (API level 26) or higher.`CompanionDeviceService` allows your app to receive data from wearables and write it to Health Connect, even when the app isn't already running. For more details on BLE best practices, see Bluetooth Low Energy overview.\\n[...]\\nFinally, create a class that extends`CompanionDeviceService`. This service handles the connection to the wearable device and receives data through BLE GATT callbacks. When new data is received, it's immediately written to Health Connect.\\n[...]\\nnext token and reserve it\\n[...]\\n.\\n- Search\\n[...]\\napp datastore\\n[...]\\nan`id\\n[...]\\na specific timestamp, and then\\n[...]\\nor update them\\n[...]\\ns datastore.\\n[...]\\nto reserve it for the next time\\n[...]\\nApps can only read data from Health Connect while they are in the foreground. When syncing data from Health Connect, access to Health Connect may be interrupted at any point. For example, your app must handle interruptions midway through a sync when reading a large amount of data from Health Connect, and continue the next time the app is opened.\\n[...]\\nYou can request that your application run in the background and read data from Health Connect. If you request the Background Read permission, your user can grant your app access to read data in the background.\",\n \"position\": 3\n },\n {\n \"url\": \"https://developers.google.com/health/libraries\",\n \"title\": \"Client libraries  |  Google Health API  |  Google for Developers\",\n \"description\": \"This page provides client library examples for accessing the Google Health API.\\n[...]\\nThe Google Health API is built on HTTP and JSON, so any standard HTTP client can\\nsend requests to it and parse the responses.\\n[...]\\nHowever, instead of creating HTTP requests and parsing responses manually, you\\nmay want to use the client library examples and downloads featured here.\\n[...]\\nprivate static final String DISCOVERY_URL = \\\"https://health.googleapis.com/$discovery/rest\\\"; // Adjust if needed\\n[...]\\nCredential credential =\\n[...]\\nreturn new Health.Builder(httpTransport,\\n[...]\\nsetRootUrl(\\n[...]\\nCOVERY_URL)\\n[...]\\nGoogleAuthorizationCodeFlow flow\\n[...]\\nnew GoogleAuthorizationCodeFlow.Builder(\\n[...]\\n- `com.google.api.client.*`: Core libraries for Google API client.\\n- `com.google.api.services.health.*`: Generated classes for the Google Health API. (You'll need to generate this based on the API's discovery document).\\n[...]\\n- `CLIENT_SECRETS_PATH`: Path to your `client_secret.json` file.\\n- `TOKENS_DIRECTORY_PATH`: Path to store the tokens.\\n- `API_KEY`: Your API key.\\n- `SCOPES`: The required permissions.\\n- `DISCOVERY_URL`: URL to get the API definition.\\n[...]\\n- `main` Method\\n[...]\\n- Initializes the Google Health API client and calls `fetchHealthData`.\\n[...]\\n- `fetchHealthData()`:\\n[...]\\n- Makes an API call to the Google Health API (replace the example with your specific method calls).\\n- Prints the response.\\n[...]\\n- Error Handling: The code includes basic `try...catch` blocks for error handling.\\n[...]\\n- Use the Google Identity Services library to handle the OAuth flow (\\n[...]\\n16.1).\\n[...]\\n- Use the initialized client to make requests to the Google Health API.\\n[...]\\nconst CLIENT_ID = 'YOUR_CLIENT_ID';\\nconst API_KEY = 'YOUR_API_KEY';\\nconst DISCOVERY_URL = 'https://health.googleapis.com/$discovery/rest'; // Replace with actual discovery URL if needed\\nconst SCOPES = 'https://www.googleapis.com/auth/health'; // Add other scopes as needed\\n[...]\\nasync function fetchHealthData() {\\n[...]\\n- Import Libraries:\\n[...]\\n- `https://apis.google.com/js/api.js`: Loads the core Google API client.\\n- `https://accounts.google.com/gsi/client`: Loads the Google Identity Services for authentication.\\n[...]\\n- Configuration:\\n[...]\\n- `CLIENT_ID`, `API_KEY`: Replace with your actual credentials.\\n- `DISCOVERY_URL`: The URL to get the API definition. You may need to adjust this based on the final Google Health API setup.\\n- `SCOPES`: Define the necessary permissions your app will need (e.g., to read health data).\\n[...]\\n- `initClient()`:\\n[...]\\n- Loads the Google API client.\\n[...]\\n- Initializes the client with your API key and discovery document.\\n- Initializes the Google Identity Services token client.\\n[...]\\n- `authorize()`:\\n[...]\\n- Checks if a token is already available.\\n- If not, it calls `tokenClient.requestAccessToken()` to start the OAuth flow.\\n[...]\\n- `fetchHealthData()`:\\n[...]\\n- Calls `authorize()` to ensure the user is authenticated.\\n- Makes an API call to the Google Health API (replace the example with your specific calls).\\n[...]\\n- Logs the response.\\n[...]\\n- Error Handling: The code includes basic `try...catch` blocks for error handling.\\n[...]\\ngoogle-auth-oauthlib\\n[...]\\n- Use the initialized client to make requests to the Google Health API.\\n[...]\\nCLIENT_SE\\n[...]\\nTS_FILE = 'path/to/\\n[...]\\n/client_secret.json\\n[...]\\n_API_\\n[...]\\nSCOPES = ['https://www.googleapis.com/auth/health'] # Add other scopes as needed\\nDISCOVERY_URL = 'https://health.googleapis.com/$discovery/rest' # Adjust if needed\\n[...]\\nTOKEN_FILE =\\n[...]\\nflow = InstalledAppFlow.from_client_secrets_file(\\n[...]\\nCLIENT_SECRETS_FILE, SCOPES\\n[...]\\ncreds = flow.run_local_server(port=0)\\n[...]\\ndef create_health_client(creds):\\n[...]\\n\\\"\\\"\\\"Creates a Google Health API client.\\\"\\\"\\\"\\nreturn googleapiclient.discovery.build(\\n'health',\\n'v1', # Replace with the actual API version if needed\\ncredentials=creds,\\ndiscoveryServiceUrl=DISCOVERY_URL,\\ndeveloperKey=API_KEY\\n[...]\\ndef fetch_health_data(client):\\n[...]\\ndata using the API client\",\n \"position\": 4\n },\n {\n \"url\": \"https://android-dot-devsite-v2-prod.appspot.com/codelabs/health-connect\",\n \"title\": \"Build a complete integration with Health Connect  |  Android health & fitness  |  Android Developers\",\n \"description\": \"With user permission, developers can securely read from and write to Health Connect using standardized schemas and API behavior. Users get full control over their privacy settings, with granular controls to see which apps are requesting access to data at any given time. The data in Health Connect is stored on-device and encrypted. Users also get the ability to shut off access or delete data they don't want on their device, and the option to prioritize one data source over another when using multiple apps.\\n[...]\\n- Health Connect APK: This is the APK that implements Health Connect. It contains both its Permissions management and Data management components. The Health Connect APK is made available directly on the user's device, making Health Connect device-centric instead of account-centric.\\n[...]\\nThe Health Connect app is responsible for handling all the requests that your application sends through the Health Connect SDK. These requests include storing data and managing its read and write access.\\n[...]\\ndepends on the Android version installed on the phone.\\n[...]\\nrecent versions of Android.\\n[...]\\nOn Android 13 (API Level 33) and lower versions, Health Connect is not part of the Android framework. Therefore, you need to install the Health Connect app from the Google Play Store. Scan the QR code to install Health Connect.\\n[...]\\n`HealthConnectManager` stores all the functions that interact with Health Connect. In this Codelab, we will guide you step by step to complete the essential functionalities. The` ```\\ndependencies {\\n // Add a dependency of Health Connect SDK\\n implementation \\\"androidx.health.connect:connect-client:1.1.0-alpha11\\\"\\n}\\n[...]\\nReading data with Health Connect is restricted to applications running in the foreground. This restriction is in place to further strengthen user privacy. It notifies and assures users that Health Connect does not have background read access to their data and that data is only read and accessed in the foreground. When the app is in the foreground, the Differential Changes API enables developers to retrieve changes made to Health Connect by deploying a Changes token.\\n[...]\\nIn`Health\\n[...]\\nthere are two\\n[...]\\nare`getChanges\\n[...]\\nThe data changes are retrieved from Health Connect\\n[...]\\nrequests them with a Changes token\\n[...]\\ndifferential data will be taken.\\n[...]\\nTo get a Changes token, send a`ChangesTokenRequest` with a set of data types you want to track\\n[...]\\ndata changes. Keep the token and use it when you want to retrieve any updates from Health Connect.\\n[...]\\nWhen you want to get changes from the last time your app synced with Health Connect, use the Changes token you got earlier and send a`getChanges` call with the token. The`ChangesResponse` returns a list of observed changes from Health Connect such as UpsertionChange and DeletionChange.\\n[...]\\nUse`healthConnectClient.aggregate` to send`AggregateRequest`. In the aggregate request, specify a set of aggregate metrics and the time range you want to get. For example,`ExerciseSessionRecord.EXERCISE_DURATION_TOTAL` and`StepsRecord.COUNT_TOTAL` provide cumulative data, while`WeightRecord.WEIGHT_AVG`,`HeartRateRecord.BPM_MAX`, and`HeartRateRecord.BPM_MIN` provide statistical data.\\n[...]\\nThis example shows how to get associated aggregation data for a specific exercise session. First, read a record using`healthConnectClient.readRecord` with a`uid`. Then, use the`startTime` and the`endTime` of the exercise session as time range and the`dataOrigin` as filters to read associated aggregations.\\n[...]\\n)\\n[...]\\n.\\n[...]\\n)\\n[...]\\n. This may or may not\\n //\\n[...]\\nuse case: In some cases, it may be\\n[...]\\nwith\\n //\\n[...]\\nother apps.\\n[...]\\nsetOf(exerciseSession.\\n[...]\\nOrigin)\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_03_XRsmmvxHDAhPdoaIj58Y2410" }, { "role": "assistant", "content": "", "reasoning": "I now have comprehensive information. Let me also get specific details on a few more things:\n\n1. MyFitnessPal API - the docs say \"We are not accepting requests for API access at this time\" - this is crucial\n2. Google Fit REST API deprecation info\n3. Fitbit Web API migration to Google Health API\n4. Health data aggregators like PulsHealth\n\nLet me extract the actual API doc pages for the key ones, and also look for any other health data aggregators.", "finish_reason": "tool_calls", "reasoning_content": "I now have comprehensive information. Let me also get specific details on a few more things:\n\n1. MyFitnessPal API - the docs say \"We are not accepting requests for API access at this time\" - this is crucial\n2. Google Fit REST API deprecation info\n3. Fitbit Web API migration to Google Health API\n4. Health data aggregators like PulsHealth\n\nLet me extract the actual API doc pages for the key ones, and also look for any other health data aggregators.", "tool_calls": [ { "id": "call_00_U4VHCcg58HwoxL3Rol6Q9018", "call_id": "call_00_U4VHCcg58HwoxL3Rol6Q9018", "response_item_id": "fc_00_U4VHCcg58HwoxL3Rol6Q9018", "type": "function", "function": { "name": "web_extract", "arguments": "{\"urls\": [\"https://github.com/sjawhar/macrofactor/blob/main/docs/api-reference.md\", \"https://api.hevyapp.com/docs/\", \"https://developers.google.com/fit/rest/v1/reference\", \"https://myfitnesspalapi.com/docs/\", \"https://dev.fitbit.com/build/reference/web-api/explore/\"]}" } }, { "id": "call_01_ESqTzMj4HmaXley5tI6e6824", "call_id": "call_01_ESqTzMj4HmaXley5tI6e6824", "response_item_id": "fc_01_ESqTzMj4HmaXley5tI6e6824", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Google Fit REST API deprecated end of service 2026 migration Health Connect\"}" } }, { "id": "call_02_Fn81VjJDRYEo99fp1pDU6556", "call_id": "call_02_Fn81VjJDRYEo99fp1pDU6556", "response_item_id": "fc_02_Fn81VjJDRYEo99fp1pDU6556", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Terra API health data aggregator REST fitness wearable integration\"}" } } ] }, { "role": "tool", "name": "web_extract", "content": "{\n \"results\": [\n {\n \"url\": \"https://github.com/sjawhar/macrofactor/blob/main/docs/api-reference.md\",\n \"title\": \"docs/api-reference.md at main · sjawhar/macrofactor\",\n \"content\": \"# MacroFactor API Reference Summary\\n\\nThis document details the reverse-engineered API schema for MacroFactor (by Stronger By Science), which utilizes a shared Firebase backend for both its Nutrition and Workout applications.\\n\\n## 🏗️ Architecture & Authentication\\nMacroFactor uses the **Firestore REST API** via the Firebase Identity Toolkit.\\n\\n* **Firebase Project ID:** `sbs-diet-app`\\n* **Base URL:** `https://firestore.googleapis.com/v1/projects/sbs-diet-app/databases/(default)/documents`\\n* **Auth Process:** Exchange email/password at the Identity Toolkit endpoint to receive a JWT `idToken`.\\n* **Header:** `Authorization: Bearer `\\n* **Bundle IDs:** Both `com.sbs.diet` and `com.sbs.train` are valid.\\n\\n## 🆔 Universal ID Scheme & Exercise Database\\nThe system uses a **32-character hex ID scheme** for all reference data (exercises, muscles, equipment).\\n* **Pattern:** All IDs contain the string `c6f170d880`.\\n* **Data Access:** Global collections are protected by Firebase App Check (403 error). However, the full database is bundled in the workout app APK as `app_file.json`.\\n* **Resolution:** A `uuidIndex` in the JSON maps 4,170 hex IDs to human-readable names.\\n\\n## 📏 Unit Conversions & Formatting\\n| Metric | Storage Format | Conversion |\\n| :--- | :--- | :--- |\\n| **Duration / Rest** | Microseconds | Divide by `1,000,000` for seconds |\\n| **Weight** | Kilograms (kg) | Always stored as kg internally |\\n| **Dates (Nutrition)** | `YYYY-MM-DD` or `MMDD` | Varies by collection |\\n| **Dates (Workouts)** | ISO 8601 | e.g., `2026-03-18T14:30:00.000Z` |\\n\\n---\\n\\n## 📂 Collections Reference\\nAll user data is located under `users/{uid}/`.\\n\\n### 🏋️ Workout History\\n**Path:** `users/{uid}/workoutHistory/{uuid}`\\nWorkouts are organized into **Blocks** (for supersets) containing **Exercises**, which contain **Sets**.\\n\\n```typescript\\n{\\n id: string,\\n startTime: string, // ISO 8601\\n duration: number, // Microseconds\\n blocks: [\\n {\\n exercises: [\\n {\\n exerciseId: string, // Hex ID\\n sets: [{\\n setType: \\\"warmUp\\\" | \\\"standard\\\" | \\\"failure\\\",\\n log: { value: { weight: number, fullReps: number, rir: number } }\\n }]\\n }\\n ]\\n }\\n ]\\n}\\n```\\n\\n### 🍎 Food Log & Nutrition\\n**Path (Log):** `users/{uid}/food/{YYYY-MM-DD}`\\n**Path (Summary):** `users/{uid}/nutrition/{YYYY}` (Keys are `MMDD`)\\n\\n| Key | Field | Key | Field |\\n| :--- | :--- | :--- | :--- |\\n| `t` | Title/Name | `p` | Protein |\\n| `b` | Brand | `e` | Carbs |\\n| `c` | Calories | `f` | Fat |\\n| `g` | Serving (g) | `h` / `mi` | Hour / Minute (Local time) |\\n\\n> **Formula for True Calories:**\\n> `(calories_raw * (userQty * (unitWeight ?? servingGrams)) / servingGrams)`\\n\\n### ⚖️ Body Metrics\\n* **Scale Weight:** `users/{uid}/scale/{YYYY}`. Keys are `MMDD`. Stores weight (`w`) and body fat (`f`).\\n* **Step Counts:** `users/{uid}/steps/{YYYY}`. Keys are `MMDD`. Stores steps (`st`) and source (`s`).\\n\\n### 📋 Training Programs\\n**Path:** `users/{uid}/trainingProgram/{programId}`\\nDefines the structure of a multi-cycle program.\\n* **Rest Days:** Identified by `blocks.length === 0`, usually named `\\\"---\\\"` with `gymId: \\\"blankSlate\\\"`.\\n* **Periodization:** `periodizedTargets` allow set/rep goals to change across cycles.\\n\\n### ⚙️ User Profiles\\n* **Gym Profiles:** `users/{uid}/gym/{uuid}`. Contains equipment lists and plate calculator settings.\\n* **Workout Profile:** `users/{uid}/profiles/workout`. Stores `activeProgramId`, bar weights, and smart warm-up toggles.\\n* **Diet Profile:** `users/{uid}/profiles/diet`. Stores toolbar and shortcut configurations.\",\n \"error\": null\n },\n {\n \"url\": \"https://api.hevyapp.com/docs/\",\n \"title\": \"Swagger UI\",\n \"content\": \"Swagger UI\\n\\nExplore\\n\\n```\\n 0.0.1 \\n```\\n\\n```\\nOAS 3.0\\n```\\n\\n## Hevy API Docs\\n\\n```\\n Welcome to Hevy's public API! We're just starting to roll this out and depending on your\\n feedback, we'll be adding more features and endpoints. Also, we make no guarantees that \\n we won't completely change the structure or abandon the project entirely so use it at\\n your own risk. Currently, this API is only available to Hevy Pro users. You can get your \\n key on our web app at https://hevy.com/settings?developer. If you have any questions,\\n please reach out to pedro@hevyapp.com 🤝.\\n\\n```\\n\\n### Workouts\\n\\nGET\\n\\n/v1/workouts\\n\\nGet a paginated list of workouts\\n\\nPOST\\n\\n/v1/workouts\\n\\nCreate a new workout\\n\\nGET\\n\\n/v1/workouts/count\\n\\nGet the total number of workouts on the account\\n\\nGET\\n\\n/v1/workouts/events\\n\\nRetrieve a paged list of workout events (updates or deletes) since a given date. Events are ordered from newest to oldest. The intention is to allow clients to keep their local cache of workouts up to date without having to fetch the entire list of workouts.\\n\\nGET\\n\\n/v1/workouts/{workoutId}\\n\\nGet a single workout’s complete details by the workoutId\\n\\nPUT\\n\\n/v1/workouts/{workoutId}\\n\\nUpdate an existing workout\\n\\n### Users\\n\\nGET\\n\\n/v1/user/info\\n\\nGet user info\\n\\n### Routines\\n\\nGET\\n\\n/v1/routines\\n\\nGet a paginated list of routines\\n\\nPOST\\n\\n/v1/routines\\n\\nCreate a new routine\\n\\nGET\\n\\n/v1/routines/{routineId}\\n\\nGet a routine by its Id\\n\\nPUT\\n\\n/v1/routines/{routineId}\\n\\nUpdate an existing routine\\n\\n### ExerciseTemplates\\n\\nGET\\n\\n/v1/exercise_templates\\n\\nGet a paginated list of exercise templates available on the account.\\n\\nPOST\\n\\n/v1/exercise_templates\\n\\nCreate a new custom exercise template.\\n\\nGET\\n\\n/v1/exercise_templates/{exerciseTemplateId}\\n\\nGet a single exercise template by id.\\n\\n### RoutineFolders\\n\\nGET\\n\\n/v1/routine_folders\\n\\nGet a paginated list of routine folders available on the account.\\n\\nPOST\\n\\n/v1/routine_folders\\n\\nCreate a new routine folder. The folder will be created at index 0, and all other folders will have their indexes incremented.\\n\\nGET\\n\\n/v1/routine_folders/{folderId}\\n\\nGet a single routine folder by id.\\n\\n### ExerciseHistory\\n\\nGET\\n\\n/v1/exercise_history/{exerciseTemplateId}\\n\\nGet exercise history for a specific exercise template\\n\\n### Measurements\\n\\nGET\\n\\n/v1/body_measurements\\n\\nGet a paginated list of body measurements for the authenticated user\\n\\nPOST\\n\\n/v1/body_measurements\\n\\nCreate a body measurement entry for a given date. Returns 409 if an entry already exists for that date.\\n\\nGET\\n\\n/v1/body_measurements/{date}\\n\\nGet a single body measurement by date\\n\\nPUT\\n\\n/v1/body_measurements/{date}\\n\\nUpdate an existing body measurement entry for a given date. All fields are overwritten; omitted fields are set to null.\\n\\n#### Schemas\\n\\nPostWorkoutsRequestSet\\n\\nPostWorkoutsRequestExercise\\n\\nPostWorkoutsRequestBody\\n\\nPostRoutinesRequestSet\\n\\nPostRoutinesRequestExercise\\n\\nPostRoutinesRequestBody\\n\\nPutRoutinesRequestSet\\n\\nPutRoutinesRequestExercise\\n\\nPutRoutinesRequestBody\\n\\nPostRoutineFolderRequestBody\\n\\nBodyMeasurement\\n\\nPutBodyMeasurement\\n\\nSet\\n\\nExercise\\n\\nExerciseHistoryEntry\\n\\nCustomExerciseType\\n\\nMuscleGroup\\n\\nEquipmentCategory\\n\\nExerciseTemplate\\n\\nCreateCustomExerciseRequestBody\\n\\nRoutineFolder\\n\\nRoutine\\n\\nUserInfo\\n\\nUserInfoResponse\\n\\nWorkout\\n\\nUpdatedWorkout\\n\\nDeletedWorkout\\n\\nPaginatedWorkoutEvents\",\n \"error\": null\n },\n {\n \"url\": \"https://developers.google.com/fit/rest/v1/reference\",\n \"title\": \"API Reference  |  Google Fit  |  Google for Developers\",\n \"content\": \"# Google Fit REST API Reference Summary\\n\\nThe Google Fit REST API allows developers to manage fitness data through five primary resource types. All URIs are relative to `https://www.googleapis.com/fitness/v1/users`.\\n\\n## 1. Users.dataSources\\nA **Data Source** is a unique stream of sensor data (raw hardware data or derived/merged data).\\n\\n### Key Methods\\n* **`create` (POST `/userId/dataSources`)**: Creates a unique data source.\\n * **Important:** Do not set `dataStreamId`; the server generates it based on source contents and the authenticated developer project number.\\n * **Custom Data Types:** Types not starting with `com.google.` are custom, readable only by the creator, and are **deprecated**.\\n* **`delete` (DELETE `/userId/dataSources/dataSourceId`)**: Fails if the source contains any data points.\\n* **`list` (GET `/userId/dataSources`)**: Lists visible data sources based on OAuth scopes.\\n* **`update` (PUT `/userId/dataSources/dataSourceId`)**: Updates a source. \\n * **Restriction:** You cannot modify `dataStreamId`, `dataType`, `type`, `dataStreamName`, or `device` (except for `version`).\\n\\n## 2. Users.dataSources.datasets\\nDatasets are containers for data points within a specific data source, defined by a time range (`datasetId`).\\n\\n### Key Methods\\n* **`patch` (PATCH `/userId/dataSources/dataSourceId/datasets/datasetId`)**: Adds data points.\\n * **Note:** This does *not* use standard patch semantics; it inserts points without replacing existing data.\\n* **`get` (GET `/userId/dataSources/dataSourceId/datasets/datasetId`)**: Returns points where `start time <= dataset end time` AND `end time >= dataset start time`.\\n* **`delete` (DELETE `/userId/dataSources/dataSourceId/datasets/datasetId`)**: \\n * Performs an **inclusive delete** of overlapping points.\\n * For consistent value types (e.g., `com.google.activity.segment`), only the overlapping portion of a straddling data point is deleted.\\n\\n## 3. Users.dataset (Aggregation)\\nUsed for high-level data analysis across multiple streams.\\n\\n* **`aggregate` (POST `/userId/dataset:aggregate`)**: \\n > \\\"Aggregates data of a certain type or stream into buckets divided by a given type of boundary. Multiple data sets of multiple types and from multiple sources can be aggregated into exactly one bucket type per request.\\\"\\n\\n## 4. Users.sessions\\nSessions represent a time interval during which a user performed a specific fitness activity.\\n\\n| Method | HTTP Request | Description |\\n| :--- | :--- | :--- |\\n| **list** | `GET /userId/sessions` | Lists previously created sessions. |\\n| **update** | `PUT /userId/sessions/sessionId` | Updates or inserts a session. |\\n| **delete** | `DELETE /userId/sessions/sessionId` | Deletes a specific session by ID. |\\n\\n## 5. Users.dataSources.dataPointChanges\\nUsed to track incremental updates to a data source.\\n\\n* **`list` (GET `/userId/dataSources/dataSourceId/dataPointChanges`)**: Queries for changes in data points for a specific source, useful for syncing local databases with the Fitness API.\\n\\n***\\n\\n### Technical Constraints & Facts\\n* **Data Stream ID:** A combination of specific fields from the data source in a specific order. If manually provided during creation, it must match the server's format exactly or the request fails.\\n* **Visibility:** The `list` method for data sources is not exhaustive; it only shows sources authorized by the current OAuth scopes.\\n* **Data Integrity:** Data points can belong to more than one dataset simultaneously.\",\n \"error\": null\n },\n {\n \"url\": \"https://myfitnesspalapi.com/docs/\",\n \"title\": \"MFP API - MFP API\",\n \"content\": \"MFP API - MFP API\\n\\n# Health, nutrition, and wellness\\n\\nWe follow a RESTful approach to designing our APIs. Requests and responses use JSON in a familiar REST style. Clients use standard HTTP methods – POST, GET, PUT, DELETE, to update resources. You can get a quick overview of our APIs before you get started.\",\n \"error\": null\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/explore/\",\n \"title\": \"Swagger UI\",\n \"content\": \"Swagger UI\\n\\nSwagger UI\",\n \"error\": null\n }\n ]\n}", "tool_call_id": "call_00_U4VHCcg58HwoxL3Rol6Q9018" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://developer.android.com/health-and-fitness/guides/health-connect/migrate/fit-apis-end-of-service\",\n \"title\": \"Google Fit Migration FAQ  |  Android health & fitness  |  Android Developers\",\n \"description\": \"- The Google Fit APIs, including the Google Fit REST API, will be deprecated in 2026.\\n- Developers cannot sign up to use these APIs as of May 1, 2024.\\n[...]\\nIf you are a developer using Google Fit APIs for Android, we recommend migrating\\nto Android Health APIs now to help provide uninterrupted service for your users.\\n[...]\\n- Health Connect : By integrating with Health Connect, your Android app can access data from a growing ecosystem of apps with just one connection. Plus, data is stored on-device, allowing the user to be in full control of their data.\\n[...]\\nGoogle Fit APIs will no longer be available for use. After the migration\\nperiod, you should have already migrated to Health Connect or\\nother Android Health APIs.\\n[...]\\n## What will happen to the Google Fit REST APIs after the migration period?\\n[...]\\nThere is no alternative to the Fit REST API.\\n\\nWe encourage Fit REST API users to migrate to the Android Health APIs. See\\nwhich one best fits your needs and users:\\n[...]\\n- Health Connect: Health Connect unifies data across Android's portfolio of devices and apps into an ecosystem, providing a common health platform for Android developers. Health Connect provides an API for reading and writing the user's health and fitness data, standardizes the data schema upon storage, and centralizes permissions control.\",\n \"position\": 1\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/health-connect/migration/fit\",\n \"title\": \"Fit migration guide | Android health & fitness\",\n \"description\": \"The Google Fit APIs are deprecated and scheduled for end of service in late\\n2026. Google offers several health and wellness products and services to help\\nyour users continue to achieve their goals after deprecation.\\n[...]\\n> Caution: The Google Fit API (including the REST API) will only be\\n> supported until the end of 2026. We recommend migrating to the Google Health API\\n> for cloud-based integrations or Health Connect for step tracking and\\n> mobile-first apps.\\n[...]\\n| Application Type | Recommended Path | Primary Reason |\\n| --- | --- | --- |\\n| Step Tracking App | Health Connect | Mobile-centric reading of aggregated steps data from various sources. |\\n| Fitness Trackers Companion App | Google Health API | Web-centric platform requiring OAuth for user integration. |\\n| Health and Fitness Platform | The Google Health API & Health Connect | Use the Google Health API for Fitbit/Google device data and Health Connect for on-device aggregated data. |\\n[...]\\n| Current Integration | Recommended Path | Availability |\\n| --- | --- | --- |\\n| Google Fit (Android & REST API) | Google Health API | Available |\\n| Reading mobile steps (with Google Fit Recording API) | Health Connect | Available |\\n| Fit API on Wear OS | Health Services | Available |\\n| Fitbit Web API | Google Health API | Available |\\n| Recording API on Mobile | Health Connect | Available |\\n| Health Connect | Keep existing integration or add the Google Health API | Available |\\n[...]\\nprefixed types | Unified\\n[...]\\n| Feature | Fit API for Android | Health Connect |\\n| --- | --- | --- |\\n| Registration | Google Cloud Console | Play Store project and health apps declaration |\\n| Authentication | OAuth 2.0 required | No OAuth required (on-device permissions) |\\n| Data storage | Cloud-centric | Device-centric (on-device) |\\n| Audience | Legacy Android developers | Modern Android mobile developers |\\n| Permissions | OAuth scopes | Android manifest permissions |\\n[...]\\n|---|---|\\n[...]\\n| Phone | Wear |\\n| 1. To show a total step count, add Health Connect to your app. The total includes mobile steps (Android 14 or higher) and steps from other apps and devices. 2. To continue showing local steps data in your app, implement writing data using Health Connect's write API. | Use Health Services: - PassiveMonitoringClient - ExerciseClient See the Health Services documentation for more on the differences between the two. |\\n[...]\\n| Phone | Wear |\\n[...]\\n| Start/stop: Not applicable. The application should track the state of ongoing sessions internally. Read/write: Transition to the Google Health API. | Start/stop: Use Health Services (ExerciseClient) Read/write: Use Health Connect with your mobile app. For specific workflows, we advise the following: - Inserting a session: Developers should use Health Connect with their mobile app and either insert an `ExerciseSessionRecord` or a `SleepSessionRecord` accordingly. |\\n[...]\\nIf your app connects to Google Fit for data sharing, follow guidance on\\nmigrating existing and new users to Health Connect or the Google Health API in\\nthese sections:\\n[...]\\n|---|---|\\n| check Do this | close Don't do this |\\n| Offer Health Connect or the Google Health API as a new option in your app. Focus on user benefits like richer data and insights, privacy, and security. | Ask users to disconnect from Google Fit. |\\n[...]\\nTo offer a similar experience to new users of your app, we recommend\\nbuilding an integration with Health Connect or the\\nGoogle Health API.\\n[...]\\nHealth Connect offers access to new data sources and types to provide a\\nricher experience for users, with data stored securely on-device. The Google\\nHealth API provides a web-centric platform for Fitbit and Google device data.\\n[...]\\n|---|---|\\n| check Do this | close Don't do this |\\n| Include Health Connect or the Google Health API in your app's setup flow. | Offer Fit as an app that users can connect to once Health Connect is available. |\",\n \"position\": 2\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/guides/health-connect/migrate/comparison-guide\",\n \"title\": \"Health Connect comparison guide  |  Android health & fitness  |  Android Developers\",\n \"description\": \"| API | Status | Audience | Storage |\\n| --- | --- | --- | --- |\\n| Health Connect | Available | Android mobile developers | On-device |\\n| Google Health API | Available | Web, server-to-server (S2S), and platform-agnostic developers | Cloud |\\n| Fitbit Web API | Transitioning | Existing Fitbit ecosystem developers | Cloud |\\n| Google Fit API | Deprecating | Legacy Google Fit (Android and REST) API developers | Cloud |\\n[...]\\nWe don't recommend migrating to Health Connect if you're an existing Google\\nFitbit Web API developer. However, if you're integrated with the Fit APIs, we\\nrecommend migrating to Health Connect only if you are a step-tracking app.\\n[...]\\n> [!NOTE]\\n> Note: The Google Fit APIs have been deprecated and we plan to support them until 2026 . See Migration guide for instructions on migrating to Health Connect.\\n[...]\\nThe following APIs are considered legacy and are being deprecated or\\ntransitioned to newer alternatives.\\n[...]\\n### Google Fit API\\n[...]\\nThe Google Fit API (including the REST API) is officially scheduled\\nfor end of service by the end of 2026. We recommend integrating with\\nHealth Connect or the Google Health API. All developers using Google Fit APIs\\nmust transition. We recommend removing Google Fit integration and encouraging\\nusers to connect to new integrations. For instructions, see the\\nFit migration guide.\",\n \"position\": 3\n },\n {\n \"url\": \"https://www.androidcentral.com/apps-software/google-has-set-a-deadline-to-shut-down-the-google-fit-api\",\n \"title\": \"Google has set a deadline to shut down the Google Fit API | Android Central\",\n \"description\": \"* Developers using Google Fit APIs need to switch to Health Connect by June 30, 2025.\\n* Google has ceased accepting new sign-ups for Google Fit API access, urging developers to transition to Health Connect.\\n* The deprecation has caused concern among developers, particularly because there's no direct replacement for the Goals API, which is used for setting daily activity targets.\\n[...]\\nApps that track your fitness with Google Fit will need an upgrade by next summer, as Google is moving to a new system called Health Connect.\\n[...]\\nGoogle effectively began phasing out Fit's developer APIs with the launch of Health Connect in 2022. Google Fit used to be the primary health platform until the company started transitioning to Health Connect, also referred to as the Android Health platform.\\n[...]\\nGoogle announced in a blog post that it is giving developers until June 30, 2025, to switch over to Health Connect (via 9to5Google). The Google Fit APIs, including the REST API, will be available until that date, \\\"giving developers ample time to migrate to Android Health.\\\"\\n[...]\\nThis means that Google is no longer accepting new sign-ups for API access. Fitness and workout apps that used to rely on Google Fit now need to switch to Health Connect before the deadline.\\n[...]\\nGoogle's move to phase out the Fit APIs has sparked concerns among developers. Although Google has provided a transition guide, it hasn't introduced a substitute for the Goals API, which lets users set daily goals for steps and heart points.\\n[...]\\n), and health\\n[...]\\n. With the company phasing\\n[...]\\nInterestingly, the Google Fit app hasn't seen any significant updates lately. The last big update was just adding Health Connect support back in 2022. This adds to the mystery surrounding the app's future.\",\n \"position\": 4\n },\n {\n \"url\": \"https://developer.android.com/health-and-fitness/health-connect/migration/fit/faq\",\n \"title\": \"Google Fit Migration FAQ | Android health & fitness\",\n \"description\": \"This document provides answers to frequently asked questions about migrating\\nfrom Google Fit APIs to Android Health APIs.\\n\\n## Who does this migration impact?\\n\\nAll developers who are using the Google Fit APIs and Google Fit REST APIs.\\n\\n## What's changing?\\n\\n- The Google Fit APIs, including the Google Fit REST API, will be deprecated in 2026.\\n- Developers cannot sign up to use these APIs as of May 1, 2024.\\n\\n## How do I get started?\\n\\nTo provide a smooth transition for your users, review the\\nMigration guide.\\n\\n## What can I do with my Google Fit APIs during the migration period?\\n\\nIf you are a developer using Google Fit APIs for Android, we recommend migrating\\nto Android Health APIs now to help provide uninterrupted service for your users.\\nAndroid Health APIs offer several advantages over the Fit APIs, including:\\n\\n- Recording steps : Android Health will provide the Recording API on mobile, which doesn't require a Google user account or the need for you to request access to API scopes. It's also a more battery-efficient way to retrieve step count data. The Recording API on Mobile is launched with steps.\\n- Health Connect : By integrating with Health Connect, your Android app can access data from a growing ecosystem of apps with just one connection. Plus, data is stored on-device, allowing the user to be in full control of their data.\\n\\n## What will happen to the Google Fit APIs after the migration period?\\n\\nGoogle Fit APIs will no longer be available for use. After the migration\\nperiod, you should have already migrated to Health Connect or\\nother Android Health APIs.\\n\\n## What will happen to the Google Fit REST APIs after the migration period?\\n\\nThere is no alternative to the Fit REST API.\\n\\nWe encourage Fit REST API users to migrate to the Android Health APIs. See\\nwhich one best fits your needs and users:\\n\\n- Health Connect: Health Connect unifies data across Android's portfolio of devices and apps into an ecosystem, providing a common health platform for Android developers. Health Connect provides an API for reading and writing the user's health and fitness data, standardizes the data schema upon storage, and centralizes permissions control.\\n- Fitbit Web API: The Fitbit Web API is a platform-agnostic interface to integrate with the Fitbit ecosystem. It gives users the ability to store, share, and manage their data directly in the cloud. In the Fitbit Web API, the user's data is tied to their Fitbit account instead of their device. This means the Fitbit Web API is account-centric instead of device-centric.\\n\\n## How do I get help?\\n\\nIf you find a bug or need help with the migration, submit your feedback using\\nour issue tracker.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_01_ESqTzMj4HmaXley5tI6e6824" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://docs.tryterra.co/reference\",\n \"title\": \"REST API Endpoints | API Reference | Terra Docs\",\n \"description\": \"DevID\\\":[]}],\\\"\\n[...]\\n\\\",\\\"info\\\":{\\\"\\n[...]\\nTerraAPI\\\",\\\"version\\\":\\\"2022.03.1\\n[...]\\n\\\"},\\\"servers\\\":[{\\\"url\\\":\\\"https://api.tryterra.co/v2\\\"}],\\\"security\\\":[{\\\"ApiKeyAuth\\\":[]},{\\\"DevID\\\":[]}],\\\"components\\\":{\\\"securitySchemes\\\":{\\\"ApiKeyAuth\\\":{\\\"type\\\":\\\"apiKey\\\",\\\"in\\\":\\\"header\\\",\\\"\\n[...]\\n\\\":\\\"x-api\\n[...]\\n}},\\\"schemas\\\":{\\\"TerraUser\\\":{\\\"$schema\\\":\\\"https://json-schema.org/draft/2\\n[...]\\n20-12/schema\\\",\\\"$id\\\":\\\"https://raw.githubusercontent.com/tryterra/openapi/refs\\n[...]\\n\\\",\\\"type\\\":\\\"object\\\",\\\"properties\\n[...]\\n\\\":{\\\"type\\\":\\\"string\\\",\\\"minLength\\\":1,\\\"description\\\":\\\"Terra identifier for the wearable connection\\n[...]\\n\\\"provider\\\":{\\\"\\n[...]\\nstring\\\",\\\"minLength\\n[...]\\n\\\":\\\"(when available)\\n[...]\\nmetadata\\\"},\\\"reference_id\\\":{\\\"type\\\":\\\"string\\\",\\\"description\\\":\\\"Connection\\n[...]\\nthe developer'\\n[...]\\nuser on the developer's platform\\\"},\\\"active\\\":{\\\"type\\\":\\\"boolean\\\",\\\"description\\\":\\\"whether the\\n[...]\\nis active or not (inactive users will not receive any data updates and are in considered \\\"}},\\\"required\\\":[\\\"user_id\\\",\\\"provider\\\"]}}},\\\"paths\\\":{\\\"/userInfo\\\":{\\\"get\\\":{\\\"tags\\\":[\\\"User\\\"],\\\"operationId\\\":\\\"User_GetInfoForUserID\\\",\\\"description\\n[...]\\nID or multiple\\n[...]\\n_id\\\",\\\"in\\\":\\\"query\\\",\\\"\\n[...]\\nID to query\\n[...]\\n\\\",\\\"schema\\\":{\\\"type\\\":\\\"string\\\"},\\\"required\\\":false\\n[...]\\nname\\\":\\\"reference_id\\\",\\\"in\\n[...]\\nsingle User object\\n[...]\\n\\\",\\\"type\\\":\\\"object\\n[...]\\n/schemas/\\n[...]\\nUser\\\"},\\\"status\\n[...]\\ntype\\\":\\\"string\\\",\\\"enum\\n[...]\\nwhen one or more parameters is malformed - an appropriate\\n[...]\\nmessage will be returned\\\",\\\"content\\\":{\\\"application/\\n[...]\\n\\\":{\\\"type\\\":\\\"\\n[...]\\n\\\",\\\"properties\\\":{\\\"\\n[...]\\na detailed message describing the\\n[...]\\n\\\":\\\"indicates that an\\n[...]\\nwhen a parameter does not\\n[...]\\n's end (e.\\n[...]\\n. user_id)\\\",\\\"\\n[...]\\n\\\":\\\"indicates that an error happened (\\n[...]\\nis error)\\\"}}}}}}}}}}}\\n[...]\\n\\\"}},\\\"required\\n[...]\\nuser_id\\\",\\\"provider\\\"]}}},\\\"paths\\\":{\\\"\\n[...]\\nsubscriptions\\\":{\\\"get\\n[...]\\n\\\":[\\\"User\\\"],\\\"operation\\n[...]\\nGetAllUserIDs\\\",\\\"\\n[...]\\n\\\"}]}}},\\n[...]\\n\\\":{\\\"$schema\\n[...]\\njson-schema\\n[...]\\n/2020-12/schema\\\",\\\"$id\\\":\\\"https://raw\\n[...]\\nusercontent.com\\n[...]\\nschemas/Athlete.\\n[...]\\n, if applicable\\n[...]\\n{\\\"openapi\\\":\\\"3.1.0\\\",\\\"info\\\":{\\\"title\\\":\\\"TerraAPI\\\",\\\"version\\\":\\\"2022.03.16\\\"},\\\"servers\\\":[{\\\"url\\\":\\\"https://api.tryterra.co/v2\\\"}],\\\"security\\\":[{\\\"ApiKeyAuth\\\":[]},{\\\"DevID\\\":[]}],\\\"components\\\":{\\\"securitySchemes\\\":{\\\"ApiKeyAuth\\\":{\\\"type\\\":\\\"apiKey\\\",\\\"in\\\":\\\"header\\\",\\\"\\n[...]\\n\\\":\\\"x-api-key\\\",\\\"\\n[...]\\nhttps://raw\\n[...]\\nobject\\\",\\\"properties\\\":{\\\"user\\n[...]\\nid\\\":{\\\"type\\n[...]\\nstring\\\",\\\"minLength\\n[...]\\n\\\"},\\\"provider\\\":{\\\"type\\n[...]\\n020\\n[...]\\nthe user, as\\n[...]\\n_max_\\n[...]\\nHeartRateZoneData\\n[...]\\nDistance covered during\\n[...]\\nlap - only relevant\\n[...]\\nassociated lap,\\n[...]\\nISO86\\n[...]\\n1 format with microsecond\\n[...]\\nZone info will be provided whenever possible. If absent, the time corresponds to the user's local time\\\"},\\\"stroke_type\\\":{\\\"$ref\\\":\\\"#/components/schemas/StrokeType\\\",\\\"description\\\":\\\"Stroke type - only relevant for swimming activities\\\"}}},\\\"StrokeType\\\":{\\\"$schema\\\":\\\"https://json-schema.org/draft/2020-12/schema\\\",\\\"$id\\\":\\\"https://raw.githubusercontent.com/tryterra/openapi/refs\\n[...]\\nschemas/StrokeType.\\n[...]\\n\\\",\\\"oneOf\\n[...]\\ntype\\\":\\\"string\\\",\\\"const\",\n \"position\": 1\n },\n {\n \"url\": \"https://docs.tryterra.co/health-and-fitness-api\",\n \"title\": \"Overview | Terra Docs\",\n \"description\": \"Terra's Health & Fitness API is your primary gateway to accessing comprehensive health data in your app from your users' wearables, devices, health apps, and medical devices.\\n[...]\\n- It standardises endpoints for authentication, requests, and data models across 500+ data sources.\\n- It's event-based: user health and fitness data is automatically pushed to your destination (e.g., webhook) after authentication. API requests are therefore only needed for historical data.\\n[...]\\n- Mechanism: Receive automated, near real-time data updates via HTTP POST requests (Webhooks) to your specified Destination endpoint.\\n- Trigger: Webhooks are typically triggered when new data is synced from a user's wearable or app to the provider's cloud service and subsequently processed by Terra.\\n- Content: Payloads include standardised JSON representing new or updated user data (e.g., a completed workout, daily summary, new sleep session).\\n- Use Case: Keep your application's data for users current without needing to poll for changes. Ideal for timely insights and responsive features.\\n[...]\\n- Mechanism: Make synchronous or asynchronous `GET` requests to specific Terra API endpoints to fetch data for a user over a defined date range.\\n- Scope: Access data from the point a user first connected their account to Terra, subject to provider limitations.\\n- Use Case: Populate user profiles, establish baselines, perform trend analysis, or backfill data.\\n- Considerations: For large data ranges (e.g., >28 days), requests are often processed asynchronously, with data delivered in chunks via Webhooks or to a specified data store.\\n[...]\\n) to facilitate the\\n[...]\\ngrant your application\\n[...]\\nto access their\\n[...]\\ndata via Terra\\n[...]\\nmanages user connections and provides unique identifiers\\n[...]\\neach connected data source account.\\n[...]\\n- Mechanism: Send data from your application to Terra via specific POST API endpoints, which then attempts to write this data to the connected user's account on the source provider's platform.\\n- Supported Operations (Examples): Planned Workouts: Upload structured workout plans that users can access and follow on their wearable devices.\\n- Provider Dependency: Only certain providers are supported - this depends on the features supported by the end provider's API. Not all data types or providers support write operations.\\n[...]\\nThe majority of Terra integrations are web-based providers (e.g., Garmin, Fitbit, Oura, Strava)\\n[...]\\n- For most providers, Terra integrates directly with their Web APIs.\\n- Whether you are building a web app or mobile app, you should integrate the API in your backend.\\n- Once a user authenticates via the API, Terra can fetch data and send payloads (e.g. to a webhook endpoint).\\n[...]\\nThe only mobile-only sources are: Apple Health, Samsung Health, and Health Connect.\\n[...]\\n- These sources do not offer Web APIs for third-party developer access.\\n- They require a mobile app with a Terra's Mobile SDK on the user's device to fetch the data.\\n- Your mobile app, equipped with Terra's Mobile SDK, will facilitate the connection to the on-device health data store (e.g., HealthKit on iOS, Health Connect on Android).\\n- The Mobile SDK then securely transmits this data to Terra for processing and delivery of payloads to your configured Destination (e.g. to a webhook endpoints).\\n[...]\\nThe vast majority of Health & Fitness API work via Terra's Web API (e.g., Garmin, Fitbit, Oura, Strava).\\n[...]\\nYou do NOT need to use the Mobile SDK for them.\\n[...]\\n-based source\\n[...]\\nLearn how to setup and configure the Health & Fitness API to receive your users' data to your preferred destination (e.g. webhook, DB, etc). This includes enabling data sources, setting up data destinations, managing API access, and understanding environments.\\n{% endstep %}\\n[...]\\nLearn how to receive automatic data updates as events, request historical information, and write data (like planned workouts) back to users' connected services.\",\n \"position\": 2\n },\n {\n \"url\": \"https://docs.tryterra.co/health-and-fitness-api/quickstart\",\n \"title\": \"Quickstart | Terra Docs\",\n \"description\": \"## Key steps to setup Health & Fitness API\\n[...]\\nFollow this short tutorial to set up event-based health data delivery via Webhooks. Learn how Terra manages user authentication and can automatically send new user data, simplifying your integration. (Other methods, like requesting historical data, are covered in the detailed guides.\\n[...]\\n#### Integration Setup\\n[...]\\nA. Add Data Sources from your Terra Dashboard\\n[...]\\n- First you need to select your data sources on your Terra dashboard. This determines:\\n- (a) What data sources are available for end-users to chose on the Terra auth widget.\\n- What data sources are automatically synced to your data destination via events.\\n[...]\\nB. Add a Data Destination in your Terra Dashboard\\n\\n- The Health & Fitness API is event- based, so the Data Destinations are where you will receive payload events:\\n- (a) New health data updates\\n- (b) Authentication events, de-auth events, etc.\\n[...]\\n### How to setup a Webhook destination?\\n[...]\\nC. Obtain your API Key & Dev-ID from your Terra Dashboard\\n[...]\\n{% hint style=\\\"info\\\" %}\\nCore concept: `user_id`\\n[...]\\nAll data is linked back to a `user_id` on Terra's side. This uniquely identifies a wearable account connection through the API and allows you to retrieve data for that wearable account. This is what Terra calls a Core concepts.\\n\\nYou will use this `user_id` in all your data-related interactions with Terra\\n{% endhint %}\\n[...]\\n{% hint style=\\\"info\\\" %}\\nCore concept: `reference_id`\\n[...]\\nYou can link a `user_id` to an entity on your end using a `reference_id`. This is a custom identifying metadata you can define on the Terra User object to link them back to a user on your app.\\n{% endhint %}\\n[...]\\n#### User Authentication\\n[...]\\n- Next you need to authenticate a user via the API to a data source (e.g. to Oura, Fitbit, Withings).\\n- Terra simplifies this by allowing you to generate a pre-built authentication widget session (by running the following code).\\n- Copy/Paste the widget session `url` into web browser. To test the authentication flow, you can choose a data sources (e.g. Fitbit), and complete the flow.\\n[...]\\nclient = Terra(\\n dev_id=\\\"\\\",\\n api_key=\\\"\\\",\\n)\\n[...]\\nresponse = client.authentication.generatewidgetsession(\\n reference_id=\\\"my_first_connection\\\",\\n auth_success_redirect_url=\\\"https://example.com/success\\\",\\n auth_failure_redirect_url=\\\"https://example.com/failure\\\",\\n)\\n[...]\\n\\\"\\n });\\n[...]\\n);\\n }\\n[...]\\n```bash\\ncurl --request POST --url https://api.tryterra.co/v2/auth/generateWidgetSession \\\\\\n --header 'dev-id: ' \\\\\\n --header 'x-api-key: ' \\\\\\n --header 'Content-Type: application/json' \\\\\\n --data '{\\n \\\"language\\\": \\\"en\\\",\\n \\\"reference_id\\\": \\\"my_first_connection\\\",\\n \\\"auth_success_redirect_url\\\": \\\"https://example.com/success\\\",\\n \\\"auth_failure_redirect_url\\\": \\\"https://example.com/failure\\\",\\n }'\\n[...]\\n#### Receive data updates\\n[...]\\n- Terra automatically sends new data to your server (e.g. webhook endpoint) when it becomes available from your users' wearables.\\n- If you're using your own Webhook destination, the following code is an example of how you can handle Webhooks.\\n[...]\\n@app.route(\\\"/consumeTerraWebhook\\\", methods=[\\\"POST\\\"])\\ndef consume_terra_webhook() -> flask.Response:\\n data = request.get_json()\\n _LOGGER.info(\\n \\\"Received webhook for user %s of type %s\\\",\\n data.get(\\\"user\\\", {}).get(\\\"user_id\\\"),\\n data[\\\"type\\\"]\\n )\\n # you can now use the incoming data in your app\\n # handleData(data)\\n[...]\\n// Webhook endpoint\\napp.post(\\\"/consumeTerraWebhook\\\", (req, res) => {\\n res.sendStatus(200); // Respond to Terra immediately\\n\\n try {\\n const data = JSON.parse(req.body.toString(\\\"utf8\\\"));\\n console.log(\\\"Received Terra Webhook Data:\\\");\\n console.log(JSON.stringify(data, null, 2));\\n } catch (err) {\\n console.error(\\\"Failed to parse webhook payload:\\\", err.message);\\n }\\n});\\n[...]\\n## Example payloads\\n[...]\\n{% tab title=\\\"Daily\\\" %}\",\n \"position\": 3\n },\n {\n \"url\": \"https://docs.tryterra.co/health-and-fitness-api/managing-user-health-data/requesting-historical-data\",\n \"title\": \"Requesting historical health data (REST API requests) | Terra Docs\",\n \"description\": \"# Requesting historical health data (REST API requests)\\n[...]\\nTerra API is event-based, meaning you don’t** need to manually request data via the API.**\\n[...]\\nFor new and ongoing data updates, Terra API automatically sends them to your configured Data Destination (e.g. Webhook, Database, or cloud storage bucket).\\n\\nIf you need historical user data, you can request it using the Health & Fitness API endpoints by specifying the user ID, data type, and time range. This allows you to request past records on demand.\\n[...]\\nare historical data\\n[...]\\n1. API Key & dev-id: Obtain your Terra API Key and dev-id from your Terra Dashboard\\n2. Destination Configured: Set up a Data Destination where Terra will send event and data updates.\\n3. Data Sources Enabled: Enable the specific data sources your app requires (e.g., activity, sleep).\\n4. Connected at least a user. Requests are done using a `user_id` and at least a date. The User must be connected via Terra's Health & Fitness API. The `user_id` is needed to make requests for historical data\\n{% endhint %}\\n[...]\\nWhen an end user first connects an account (e.g. wearable, device, health app), you will by default only receive data from that point onwards.\\n[...]\\nIf you would like to build a historical health & fitness profile of the user, to establish baselines for statistics, or for any other calculations, you can make a request to Terra for data from prior to the user's authentication.\\n[...]\\n## 3. Request Data via the API\\n[...]\\nTo request historical data from your Backend, you need to call one of the Data Retrieval Endpoints. Refer to the API endpoints section for further details on usage.\\n[...]\\nTo request historical data, the following request parameters are required:\\n[...]\\n- `user_id` (required)\\n- `start_date` (required)\\n[...]\\nTerra's Data Retrieval endpoints include many other useful and important parameters.\\n[...]\\n1. `with_samples` must be set to `true` to receive granular data (refer to Integration setup)\\n2. `to_webhook` must be set to `true` if you want to receive data asynchronously to your Destination. For synchronous data retrieval (if your use case is time-sensitive), just set this parameter to `false`.\\n[...]\\n```python\\n@app.post(\\\"/webhook\\\")\\nasync def webhook_handler(request: Request):\\n payload = await request.json()\\n \\n if payload.get(\\\"type\\\") == \\\"auth\\\" and payload.get(\\\"status\\\") == \\\"success\\\":\\n # Calculate date range, to get data from 28 days ago to today\\n start_date = (datetime.utcnow() - timedelta(days=28)).strftime('%Y-%m-%d')\\n end_date = (datetime.utcnow() + timedelta(days=1)).strftime('%Y-%m-%d')\\n headers = {\\n \\\"x-api-key\\\": os.getenv(\\\"TERRA_API_KEY\\\"), \\n \\\"dev-id\\\": os.getenv(\\\"TERRA_DEVELOPER_ID\\\")\\n }\\n endpoints = [\\n \\\"/activity\\\", \\n \\\"/daily\\\", \\n \\\"/sleep\\\", \\n \\\"/body\\\"\\n ]\\n\\n # Fetch data from each endpoint\\n results = {}\\n for endpoint in endpoints:\\n try:\\n response = requests.get(\\n f\\\"{TERRA_API_URL}{endpoint}\\\", \\n headers=headers, \\n params={\\n \\\"start_date\\\": start_date, \\n \\\"end_date\\\": end_date,\\n \\\"to_webhook\\\": True\\n }\\n )\\n response.raise_for_status()\\n results[endpoint] = response.json()\\n except requests.HTTPError as e:\\n raise HTTPException(status_code=response.status_code, detail=f\\\"Error fetching data from {endpoint}\\\")\\n\\n return {\\\"message\\\": \\\"Data fetched successfully\\\", \\\"data\\\": results}\\n \\n return {\\\"message\\\": \\\"Webhook type or status did not match criteria\\\"}\\n[...]\\n### Request longer time ranges\\n[...]\\n### Requests with >28 days Time Ranges\\n[...]\\nFor time ranges longer than 28 days, Terra will default to sending the data asynchronously, even if `to_webhook` is set to `false`.\",\n \"position\": 4\n },\n {\n \"url\": \"https://docs.tryterra.co/\",\n \"title\": \"What is Terra API? | Terra Docs\",\n \"description\": \"Terra is a unified API for health and wearable data.\\n[...]\\nWe make it simple for developers to connect their applications to a vast ecosystem of fitness trackers, smartwatches, and medical devices without building or maintaining individual integrations.\\n[...]\\nAccessing health data is complex. Each device and platform (like Garmin, Fitbit, Apple Health, Oura) has its own API and data formats.\\n[...]\\nOne unified API to access standardised data from hundreds of sources. We handle the complexity of:\\n[...]\\n- Integrating with numerous providers.\\n- Normalising diverse data formats.\\n- Managing different authentication methods.\\n[...]\\nThe Health & Fitness API is Terra's main product. It integrate 500+ health data sources (including Oura, Garmin, Withings and other). It standardises access to varied data, such as activity, sleep, heart rate, readiness.\\n[...]\\n| | | | | | |\\n| --- | --- | --- | --- | --- | --- |\\n| Health & Fitness API | What it is: Access rich current and historical user health data like activity, sleep, and workouts. | Use for: Comprehensive wellness insights, user trend analysis. | Supports: Garmin, Fitbit, Oura, Apple Health, Google Fit, and 500+ more. | /pages/u4aCTkJiebhGE1aqPS8y | /files/OA6ebOIMvjybLZB2Z22R |\\n[...]\\nYou can also explore additional solutions. These includes RealTime Streaming of raw data (e.g. Steps, Heart Rate) from specific device models, or the Teams API which provides unified access to athlete monitoring platforms such as Vald and Catapult.\\n[...]\\n| | | | | | |\\n| --- | --- | --- | --- | --- | --- |\\n| Streaming API | What it is: Get live, real-time raw sensor data such as heart rate and distance from specific BLE & ANT+ devices to your websocket listener. | Used for: Live workout feedback, real-time monitoring, interactive experiences | Supports: Apple Watch, BLE/ANT+ devices (e.g., heart rate monitors). | /files/72Q7VghPZB8ViJIZtEeh | /pages/GrQY4g9ptjveDAEhrNxp |\\n[...]\\n| Teams API [BETA] | What it is: Aggregate and analyse data for groups or teams across across matches and individual athlete tests. | Used for: Athlete performance tracking, team wellness dashboards. | Supports: Specialist athlete monitoring systems (e.g. Vald, Catapult, etc.) | /files/xwp3C68Jm22AMdaEBH76 | /pages/ltjCh5hpT4pOLatHrhtJ |\\n[...]\\n- Proceed to Account setup & API keys to get your credentials.\\n- We suggest you start with the Health & Fitness API and connecting one user.\\n- We also recommend exploring our Core Concepts to understand how Terra works.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_02_Fn81VjJDRYEo99fp1pDU6556" }, { "role": "assistant", "content": "", "reasoning": "Now I have comprehensive data. Let me also get the Fitbit Web API data types and Cronometer details, and the new Google Health API (which replaces Fitbit).", "finish_reason": "tool_calls", "reasoning_content": "Now I have comprehensive data. Let me also get the Fitbit Web API data types and Cronometer details, and the new Google Health API (which replaces Fitbit).", "tool_calls": [ { "id": "call_00_I91lKriI5Exg444UVNCv8682", "call_id": "call_00_I91lKriI5Exg444UVNCv8682", "response_item_id": "fc_00_I91lKriI5Exg444UVNCv8682", "type": "function", "function": { "name": "web_extract", "arguments": "{\"urls\": [\"https://dev.fitbit.com/build/reference/web-api/developer-guide/\",\"https://developers.google.com/health/endpoints\",\"https://pypi.org/project/cronometer-api-mcp/0.1.3/\"]}" } }, { "id": "call_01_5hccKQDOZgYBpvD8lBcN8309", "call_id": "call_01_5hccKQDOZgYBpvD8lBcN8309", "response_item_id": "fc_01_5hccKQDOZgYBpvD8lBcN8309", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Fitbit Web API data types list activity sleep heart rate nutrition weight body endpoints\"}" } } ] }, { "role": "tool", "name": "web_extract", "content": "{\n \"results\": [\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/developer-guide/\",\n \"title\": \"Developer Guide\",\n \"content\": \"Developer Guide\\n\\n# Fitbit Web API Developer Guide\\n\\nThe Fitbit Web API Developer Guide is intended to help a developer get started using the the Web API, along with providing additional content on implementing the endpoints. Anyone may use the Web API to build integrations with the Fitbit data services, so long as their application complies with:\\n\\n- the Fitbit Platform Terms of Service, Fitbit User Data and Developer Policy, and the Fitbit user consents to share their data with the developer’s application for access to Fitbit user data, and\\n- the Fitbit Platform Terms of Service, the Google APIs Terms of Service, Google API Services User Data Policy, OAuth 2.0 Policies, Fitbit User Data and Developer Policy, and the Fitbit user consents to share their data with the developer's application for access to Google user data.\\n\\nThis guide provides the following resources,\\n\\n- Getting Started explains how to create a Fitbit developer account and register an application.\\n- Authorization steps you through implementing the Authorization Code Grant Flow with PKCE; the recommended authorization flow for requesting access to Fitbit user data.\\n- Application Design contains various topics to consider when building your application, such as data types, headers, localization, the rate limit, etc.\\n- Using Subscriptions explains the importance of webhooks and the best practices for implementing them in your solution.\\n- Best Practices contains suggestions from the support and engineering teams on concepts requested by the developer community.\\n- Libraries and Sample Code provides a list of OAuth2 libraries and sample code our developer community found and has successfully used.\\n\\nIf you have problems using the Web APIs, check out the Troubleshooting Guide for a solution before contacting the Web API Developer Support team.\\n\\nActive Zone Minutes Time Series\",\n \"error\": null\n },\n {\n \"url\": \"https://developers.google.com/health/endpoints\",\n \"title\": \"Endpoints  |  Google Health API  |  Google for Developers\",\n \"content\": \"# Google Health API Endpoints Summary\\n\\nThis guide outlines the REST API conventions, data handling standards, and common tasks for the Google Health API.\\n\\n## 1. REST API Conventions\\nThe API adheres to Google API Improvement Proposals (AIP), specifically **AIP-127** (Transcoding) and **AIP-131 through 135** (Standard Methods).\\n\\n### Data Mapping Methods\\n| Feature | Query Parameters | Request Body |\\n| :--- | :--- | :--- |\\n| **Primary Use** | Searching, filtering, pagination (`GET`, `LIST`, `DELETE`). | Modifying state or large data (`POST`, `PATCH`, `PUT`). |\\n| **Visibility** | Visible in browser history/server logs. | Hidden from the URL. |\\n| **Complexity** | Limited to flat or repeated structures. | Supports deeply nested JSON objects. |\\n| **Encoding** | Must be URL-encoded (e.g., space = `%20`). | Standard JSON encoding. |\\n\\n* **The Hybrid Case:** `PATCH` operations use both. The URL identifies the resource, the body contains updated data, and a query parameter (e.g., `update_mask`) specifies fields to change.\\n\\n## 2. Technical Requirements & Standards\\n\\n### Headers\\nRequired for all requests:\\n```http\\nAuthorization: Bearer access-token\\nAccept: application/json\\n```\\n\\n### Dates and Time\\n* **Format:** Standard dates use `YYYY-MM-DD`.\\n* **ISO-8601:** Supported by the Nutrition API (Years 0000-9999).\\n* **Naming Convention Conflict:** \\n * **Endpoints:** Use **kebab-case** (e.g., `body-fat`).\\n * **Filter Parameters:** Use **snake_case** (e.g., `body_fat`).\\n\\n## 3. API Task Index & Examples\\n\\n### Identity Management\\n**Task:** Get Fitbit or Google user IDs.\\n* **Insight:** OAuth token responses do not contain user IDs. Call `getIdentity` immediately after consent to store both `legacyUserId` (Fitbit) and `healthUserId` (Google) for forward compatibility.\\n```http\\nGET https://health.googleapis.com/v4/users/me/identity\\n```\\n\\n### Data Retrieval & Filtering\\n* **Intraday Data:** Use the `list` endpoint for specific data types (e.g., `steps`) to get detailed intervals.\\n* **Filtering by Civil Time:**\\n ```http\\n GET .../dataPoints?filter=steps.interval.civil_start_time >= \\\"2026-03-04T00:00:00\\\"\\n ```\\n* **Filtering by Physical Time:**\\n ```http\\n GET .../body-fat/dataPoints?filter=body_fat.sample_time.physical_time >= \\\"2026-03-01T00:00:00Z\\\"\\n ```\\n* **Filtering by Source (Wearables):** Use the `reconcile` endpoint to get data from specific \\\"data source families.\\\"\\n ```http\\n GET .../sleep/dataPoints:reconcile?dataSourceFamily=users/me/dataSourceFamilies/google-wearables&filter=sleep.interval.civil_end_time >= \\\"2026-03-03\\\"\\n ```\\n\\n### Data Aggregation\\n* **RollUp:** Aggregates data points based on a `windowSize` (in seconds) over a UTC range.\\n* **DailyRollUp:** Aggregates data across single or multiple days. Requires a closed-open civil time range in the request body.\\n ```json\\n {\\n \\\"range\\\": {\\n \\\"start\\\": { \\\"date\\\": { \\\"year\\\": 2026, \\\"month\\\": 2, \\\"day\\\": 26 }, \\\"time\\\": { \\\"hours\\\": 0 } },\\n \\\"end\\\": { \\\"date\\\": { \\\"year\\\": 2026, \\\"month\\\": 2, \\\"day\\\": 26 }, \\\"time\\\": { \\\"hours\\\": 23 } }\\n },\\n \\\"windowSizeDays\\\": 1\\n }\\n ```\\n\\n### Data Modification\\n* **Insert/Update:** Use the `PATCH` endpoint.\\n * *Example:* Updating a `body-fat` reading with `recordingMethod: \\\"ACTIVELY_MEASURED\\\"`.\\n* **Delete:** Use the `batchDelete` endpoint with an array of resource names.\\n ```json\\n POST https://health.googleapis.com/v4/users/me/dataTypes/body-fat/dataPoints:batchDelete\\n {\\n \\\"names\\\": [\\\"users/ID/dataTypes/body-fat/dataPoints/12345\\\"]\\n }\\n ```\",\n \"error\": null\n },\n {\n \"url\": \"https://pypi.org/project/cronometer-api-mcp/0.1.3/\",\n \"title\": \"cronometer-api-mcp v0.1.3\",\n \"content\": \"# cronometer-api-mcp v0.1.3 Summary\\n\\n`cronometer-api-mcp` is an MCP (Model Context Protocol) server that allows AI models to interact with Cronometer nutrition data. It utilizes a reverse-engineered mobile REST API, providing a more stable and cleaner JSON-based alternative to web-scraping or GWT-RPC methods.\\n\\n## 🛠 Key Features\\n- **Food Logging:** View, add, and remove diary entries (including meal groups).\\n- **Nutrition Analysis:** Access daily macro/micro totals and nutrition scores with confidence levels.\\n- **Database Search:** Search the Cronometer food database and retrieve detailed nutrition profiles.\\n- **Management Tools:** Copy previous days, mark days complete, and create custom foods.\\n- **Advanced Tracking:** Access macro target schedules and fasting statistics/history.\\n\\n## 🚀 Quick Start & Configuration\\n\\n### Installation\\nThe project requires **Python >=3.14** and uses `uv` for package management.\\n```bash\\ncurl -LsSf https://astral.sh/uv/install.sh | sh\\nexport CRONOMETER_USERNAME=\\\"your@email.com\\\"\\nexport CRONOMETER_PASSWORD=\\\"your-password\\\"\\n```\\n\\n### Client Configuration\\nYou can run the server on-demand using `uvx`.\\n\\n**Claude Desktop (`claude_desktop_config.json`):**\\n```json\\n{\\n \\\"mcpServers\\\": {\\n \\\"cronometer\\\": {\\n \\\"command\\\": \\\"uvx\\\",\\n \\\"args\\\": [\\\"cronometer-api-mcp\\\"],\\n \\\"env\\\": {\\n \\\"CRONOMETER_USERNAME\\\": \\\"your@email.com\\\",\\n \\\"CRONOMETER_PASSWORD\\\": \\\"your-password\\\"\\n }\\n }\\n }\\n}\\n```\\n\\n## 🧰 Available Tools\\n\\n| Category | Tools |\\n| :--- | :--- |\\n| **Log & Nutrition** | `get_food_log`, `get_daily_nutrition`, `get_nutrition_scores` |\\n| **Search & Details** | `search_foods`, `get_food_details` |\\n| **Diary Management** | `add_food_entry`, `remove_food_entry`, `add_custom_food`, `copy_day`, `mark_day_complete` |\\n| **Targets & Fasting** | `get_macro_targets`, `get_fasting_history`, `get_fasting_stats` |\\n\\n*Note: All date parameters use `YYYY-MM-DD` format.*\\n\\n## 🌐 Remote Deployment\\nThe server supports remote deployment (Dokku/Heroku) with **OAuth 2.1 (PKCE)** for use with Claude.ai.\\n\\n### Essential Environment Variables\\n- `CRONOMETER_USERNAME` / `CRONOMETER_PASSWORD`: Account credentials.\\n- `MCP_TRANSPORT`: `stdio` (default), `sse`, or `streamable-http`.\\n- `MCP_AUTH_TOKEN`: Bearer token for remote authentication.\\n- `MCP_OAUTH_CLIENT_ID` / `MCP_OAUTH_CLIENT_SECRET`: For remote client connections.\\n- `MCP_BASE_URL`: Public URL for OAuth metadata.\\n\\n## 🔍 Technical Implementation\\nThe server communicates with `mobile.cronometer.com` using two specific protocols discovered via static analysis of the Android APK and traffic interception:\\n- **v2 (`POST /api/v2/*`)**: JSON-body auth; used for search, diary read/write, and nutrition.\\n- **v3 (`DELETE /api/v3/user/{id}/*`)**: Header-based auth (`x-crono-session`); used specifically for diary entry deletion.\\n\\n### Python API Example\\nThe client can be used directly in Python scripts:\\n```python\\nfrom cronometer_api_mcp.client import CronometerClient\\nclient = CronometerClient()\\n\\n# Search and Log\\nresults = client.search_food(\\\"chicken breast\\\")\\nfood = client.get_food(results[0][\\\"id\\\"])\\nclient.add_serving(food_id=food[\\\"id\\\"], measure_id=food[\\\"defaultMeasureId\\\"], grams=200)\\n```\\n\\n## 📦 Metadata\\n- **Author:** Randy\\n- **License:** MIT\\n- **Dependencies:** `httpx >=0.27.0`, `mcp >=1.0.0`, `uvicorn >=0.30.0`\\n- **Status:** Alpha (3)\",\n \"error\": null\n }\n ]\n}", "tool_call_id": "call_00_I91lKriI5Exg444UVNCv8682" }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/explore/\",\n \"title\": \"Swagger UI - Fitbit\",\n \"description\": \"Swagger UI\\n\\nSwagger UI\",\n \"position\": 1\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/activity\",\n \"title\": \"Activity\",\n \"description\": \"The Activity endpoints are used to query and/or modify a Fitbit user's daily activity data. The information returned is the step count, distance, elevation, floors, calories burned, active minutes, activity goals, exercise details, etc. The Activity endpoints support returning Intraday data (see Intraday).\\n[...]\\n- Get Activity Goals retrieves\\n[...]\\nuser's daily or weekly\\n[...]\\n- Get Activity Log List retrieves a list of the user's recorded activities, and the activity details.\\n[...]\\n- Get Activity TCX retrieves a record activity in TCX format.\\n[...]\\n- Get Activity Type retrieves the details for a single activity from the Fitbit activities database.\\n[...]\\n- Get All Activity Types retrieves the details for all activities from the Fitbit activities database.\\n[...]\\n- Get Daily Activity Summary retrieves a summary of the user's activity for a specific date.\\n[...]\\nGet Frequent Activities\\n[...]\\n- Get Lifetime Stats retrieves a user's activity statistics.\\n[...]\\n- Get Recent Activity Types retrieves a summary for the activities the user recorded, recently.\\n[...]\\nthe ground contact time and cadence for run workouts\",\n \"position\": 2\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/body\",\n \"title\": \"Fitbit Development: Body\",\n \"description\": \"The Body endpoints are used for querying and modifying the user's body fat and weight data.\\n\\nThe endpoints available in this section are\\n[...]\\n- Get Weight Log retrieves a user's weight log.\\n- Get Body Fat Log retrieves a user's body fat log.\\n- Get Body Goals retrieves a user's body fat goal.\\n- Delete Weight Log deletes a user's weight log.\\n- Delete Body Fat Log deletes a user's body fat log.\\n- Create Weight Log creates a user's weight log.\\n- Create Weight Goal creates or updates a user's weight goal.\\n- Create Body Fat Log creates a user's body fat log.\\n- Create Body Fat Goal creates or updates a user's body fat goal.\\n[...]\\nBody Time Series\",\n \"position\": 3\n },\n {\n \"url\": \"https://dev.fitbit.com/blog/2022-12-06-announcing-new-data-types\",\n \"title\": \"7 New Data Types in Fitbit Web API\",\n \"description\": \"Fitbit Web API offers a range of data types like Activity, Body, Sleep, Nutrition, Devices, Heart Rate, Friends, but we focused on expanding our open API to include in-depth health metrics this year. These new data types were top requests from our developers. We addressed these requests and have significantly expanded our data type support through 2022 with 7 new data types, with the latest one available today.\\n[...]\\nSpO2 (Oxygen Saturation) is a measurement of your blood oxygen level, recorded by body sensors while a\\n[...]\\ncan use the following API endpoints when integrating the SpO2 data type:\\n[...]\\n## Heart Rate Variability (HRV)\\n[...]\\nThe Heart Rate Variability (HRV) endpoints are used for querying the user’s heart rate variability data. Developers can request the following API endpoints when integrating the HRV data type:\\n[...]\\nGet HRV Summary\\n[...]\\nGet HRV Summary\\n[...]\\n## Breathing Rate\\n[...]\\nBreathing Rate or Respiratory Rate is a measurement of your average breaths per minute at night, recorded by body sensors in Fitbit smartwatches, Google Pixel Watch, and Fitbit fitness trackers. The Breathing or Respiratory API is for research use or investigational use only, and is not intended for clinical or diagnostic purposes. Developers can use the following API endpoints when integrating the Breathing Rate data type:\\n[...]\\nBreathing Rate Summary\\n[...]\\nVO2 Max\\n[...]\\n## Active Zone Minutes (AZM)\\n[...]\\nThe Active Zone Minutes (AZM) Time Series endpoints are used for querying the user's heart-pumping activity throughout the day. Developers can request the following API endpoints when integrating the AZM data type:\",\n \"position\": 4\n },\n {\n \"url\": \"https://dev.fitbit.com/build/reference/web-api/developer-guide\",\n \"title\": \"Developer Guide\",\n \"description\": \"The Fitbit Web API Developer Guide is intended to help a developer get started using the the Web API, along with providing additional content on implementing the endpoints. Anyone may use the Web API to build integrations with the Fitbit data services, so long as their application complies with:\\n[...]\\n- Application Design contains various topics to consider when building your application, such as data types, headers, localization, the rate limit, etc.\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_01_5hccKQDOZgYBpvD8lBcN8309" }, { "role": "assistant", "content": "", "reasoning": "Now I have all the data I need. Let me compile the comprehensive report. Let me also quickly look up the Google Health API data types to understand what data is accessible through it, since it's the replacement for Fitbit Web API.", "finish_reason": "tool_calls", "reasoning_content": "Now I have all the data I need. Let me compile the comprehensive report. Let me also quickly look up the Google Health API data types to understand what data is accessible through it, since it's the replacement for Fitbit Web API.", "tool_calls": [ { "id": "call_00_oGVGnEVqryiKV43jtQXd5191", "call_id": "call_00_oGVGnEVqryiKV43jtQXd5191", "response_item_id": "fc_00_oGVGnEVqryiKV43jtQXd5191", "type": "function", "function": { "name": "web_search", "arguments": "{\"limit\": 5, \"query\": \"Google Health API data types list activity sleep heart rate nutrition steps body 2025\"}" } } ] }, { "role": "tool", "name": "web_search", "content": "{\n \"success\": true,\n \"data\": {\n \"web\": [\n {\n \"url\": \"https://developers.google.com/health/data-types\",\n \"title\": \"Data types - Health API - Google for Developers\",\n \"description\": \"The following table contains the full list of data types, with several columns\\nto help you understand the representation of each type in the Google Health API,\\nas well as the scope each is available under.\\n[...]\\nImportant: The format of data type identifiers differs when the data type has more than one word. In an endpoint, the data type name must be in kebab case, such as `body-fat`. In a filter parameter, however, the data type name must be in snake case, such as `body_fat`.\\n[...]\\n| Data type `dataType` `filter` parameter | Record type | Available operations | Scope | Webhook support |\\n| --- | --- | --- | --- | --- |\\n| Active Minutes `active-minutes` `active_minutes` | Interval | reconcile, rollup, dailyRollup | activity_and_fitness | |\\n[...]\\n| Activity Level `activity-level` `activity_level` | Interval | list, reconcile | activity_and_fitness | |\\n[...]\\n| Body Fat `body-fat` `body_fat` | Sample | list, get, reconcile, rollup, dailyRollup, create, update, batchDelete | health_metrics_and_measurements | Yes |\\n[...]\\n| Calories In Heart Rate Zone `calories-in-heart-rate-zone` `calories_in_heart_rate_zone` | Interval | rollup, dailyRollup | activity_and_fitness | Yes |\\n[...]\\n| Daily Heart Rate Variability `daily-heart-rate-variability` `daily_heart_rate_variability` | Daily | list, reconcile | health_metrics_and_measurements | Yes |\\n[...]\\n| Daily Heart Rate Zones `daily-heart-rate-zones` `daily_heart_rate_zones` | Daily | reconcile | health_metrics_and_measurements | Yes |\\n[...]\\n| Daily Respiratory Rate `daily-respiratory-rate` `daily_respiratory_rate` | Daily | list, reconcile | health_metrics_and_measurements | |\\n[...]\\n| Daily Resting Heart Rate `daily-resting-heart-rate` `daily_resting_heart_rate` | Daily | list, reconcile | health_metrics_and_measurements | Yes |\\n[...]\\n| Daily Sleep Temperature Derivations `daily-sleep-temperature-derivations` `daily_sleep_temperature_derivations` | Daily | list, reconcile | health_metrics_and_measurements | Yes |\\n[...]\\nexercise` | Session |\\n[...]\\n, create,\\n[...]\\n| Heart Rate `heart-rate` `heart_rate` | Sample | list, reconcile, rollup, dailyRollup | health_metrics_and_measurements | Yes |\\n[...]\\n| Hydration Log `hydration-log` `hydration_log` | Session | list, get, reconcile, rollup, dailyRollup, create, update, batchDelete | nutrition | |\\n[...]\\n| Respiratory Rate Sleep Summary `respiratory-rate-sleep-summary` `respiratory_rate_sleep_summary` | Sample | list, reconcile | health_metrics_and_measurements | |\\n[...]\\n| Sleep `sleep` `sleep` | Session | list, get, reconcile, create, update, batchDelete | sleep | Yes |\\n[...]\\n| Steps `steps` `steps` | Interval | list, reconcile, rollup, dailyRollup | activity_and_fitness | Yes |\\n[...]\\nup | activity_and_fitness | |\\n[...]\\n| Weight `weight` `weight` | Sample | list,\\n[...]\\n, reconcile, rollup, dailyRollup, create, update, batchDelete | health_metrics_and_measurements | Yes |\",\n \"position\": 1\n },\n {\n \"url\": \"https://developers.google.com/health/release-notes\",\n \"title\": \"Release notes  |  Google Health API  |  Google for Developers\",\n \"description\": \"### New Data Types\\n[...]\\n- Activity & Fitness : `swim-lengths-data`\\n- Health Metrics & Measurements : `height`\\n[...]\\n- Automatic subscription creation when a subscriber is registered.\\n- Manually manage your subscriptions using the `project.subscribers` endpoints\\n- Notification support for the data types `activeZoneMinutes`, `altitude`, `bodyFat`, `caloriesInHeartRateZone`, `dailyHeartRateVariability`, `dailyHeartRateZones`, `dailyOxygenSaturation`, `dailyRestingHeartRate`, `dailySleepTemperatureDerivations`, `distance`, `exercise`, `floors`, `heartRate`, `sleep`, `steps`, `totalCalories`, and `weight`.\\n[...]\\n- Default Intraday Support: Retrieve granular, intraday data by default using the list endpoint, eliminating extra steps.\\n[...]\\n### Supported Data Types\\n[...]\\nData Types Supporting Read:\\n[...]\\n- Activity & Fitness: Active Minutes, Active Zone Minutes, Activity Level, Altitude, Calories in Heart Rate Zones, Daily VO2 Max, Distance, Exercise, Floors, Run VO2 Max, Sedentary Period, Steps, Time in Heart Rate Zone, Total Calories, VO2 Max\\n[...]\\n- Health Metrics & Measurements: Body Fat, Daily Heart Rate Variability, Daily Heart Rate Zones, Daily Oxygen Saturation, Daily Respiratory Rate, Daily Resting Heart Rate, Daily Sleep Temperature Derivations, Heart Rate, Heart Rate Variability, Oxygen Saturation, Respiratory Rate Sleep Summary, Weight\\n[...]\\n- Identity: Returns the Fitbit user ID and the Google user ID\\n- Location: GPS data based on a recorded exercise exposed in TCX format\\n- Nutrition: Hydration Log\\n- Profile: Users basic profile information\\n- Settings: Users configured device and mobile app settings\\n- Sleep: Classic and Stages sleep logs\\n[...]\\nData Types Supporting Write:\\n[...]\\nYou can write and modify data for these data types:\\n[...]\\n- Activity & Fitness: Exercise\\n- Health Metrics & Measurements: Body Fat, Weight\\n- Profile\\n- Settings\\n- Sleep\\n[...]\\nThe following endpoints are available to manage subscriptions,\\nusers, and health & fitness data:\\n[...]\\n- `users`: `getIdentity`, `getProfile`, `getSettings`, `updateProfile`, and `updateSettings` methods for identity and profile management.\\n- `users.dataTypes.dataPoints`: `batchDelete`, `dailyRollUp`, `list`, `patch`, `reconcile`, and `rollUp` methods for comprehensive data type management.\",\n \"position\": 2\n },\n {\n \"url\": \"https://developers.google.com/health/endpoints\",\n \"title\": \"Endpoints  |  Google Health API  |  Google for Developers\",\n \"description\": \"Query parameters are used when the data is part of the URL. This is primarily\\nfor `GET` requests (fetching a resource) or `LIST` requests\\n(filtering/pagination), but is also used for `DELETE` operations.\\n[...]\\nAll dates in the Google Health API are displayed in the format `YYYY-MM-DD`. The\\nNutrition API supports the ISO-8601 standard for date values with the following\\nconditions:\\n[...]\\n### Get intraday or detailed data collected throughout a day\\n[...]\\nUse the `list`\\nendpoint for a specific\\ndata type to get intraday or detailed data collected throughout the day in\\nsupported intervals for that data type.\\n[...]\\n```\\nGET https://health.googleapis.com/v4/users/me/dataTypes/steps/dataPoints\\nAuthorization: Bearer access-token\\nAccept: application/json\\n[...]\\n### Filter data by an interval civil start time\\n[...]\\nUse the `list` endpoint with a `filter` parameter to filter data by civil time\\nor an interval.\\n[...]\\nImportant: The format of data type identifiers differs when the data type has more than one word. In an endpoint, the data type name must be in kebab case, such as `body-fat`. In a filter parameter, however, the data type name must be in snake case, such as `body_fat`.\\n[...]\\nhealth.googleapis.com\\n[...]\\n### Filter data by a sample observation physical time\\n[...]\\nUse the `list` endpoint with a `filter` parameter to filter data by sample\\nobservation physical time.\\n[...]\\nImportant: The format of data type identifiers differs when the data type has more than one word. In an endpoint, the data type name must be in kebab case, such as `body-fat`. In a filter parameter, however, the data type name must be in snake case, such as `body_fat`.\\n[...]\\n### Filter data by data sources such as wearables\\n[...]\\nUse the `reconcile`\\nendpoint to get\\ndata by a \\\"data source family\\\" in a reconciled stream.\\n[...]\\nImportant: The format of data type identifiers differs when the data type has more than one word. In an endpoint, the data type name must be in kebab case, such as `body-fat`. In a filter parameter, however, the data type name must be in snake case, such as `body_fat`.\\n[...]\\nHere's an example of filtering only the tracker-recorded sleep for the day after\\n2026-03-03:\\n[...]\\n```\\nGET https://health.googleapis.com/v4/users/me/dataTypes/sleep/dataPoints:reconcile?dataSourceFamily=users/me/dataSourceFamilies/google-wearables&filter=sleep.interval.civil_end_time >= \\\"2026-03-03\\\"\\nAuthorization: Bearer access-token\\nAccept: application/json\\n[...]\\n{\\n \\\"dataPoints\\\": [\\n {\\n \\\"name\\\": \\\"users/2515055256096816351/dataTypes/sleep/dataPoints/2724123844716220216\\\",\\n \\\"dataSource\\\": {\\n \\\"recordingMethod\\\": \\\"DERIVED\\\",\\n \\\"device\\\": {\\n \\\"displayName\\\": \\\"Charge 6\\n[...]\\n},\\n \\\"platform\\\": \\\"FITBIT\\n[...]\\n},\\n \\\"sleep\\\": {\\n \\\"interval\\\": {\\n \\\"startTime\\\": \\\"2026-03-03T20:57:30Z\\\",\\n[...]\\nstartUtcOffset\\\": \\\"0s\\\",\\n \\\"endTime\\\": \\\"2026-03-04T04:41:30Z\\\",\\n \\\"endUtcOffset\\\": \\\"0s\\\"\\n },\\n \\\"type\\\": \\\"STAGES\\\",\\n \\\"stages\\\": [\\n {\\n \\\"startTime\\\": \\\"2026-03-03T20:57:30Z\\\",\\n \\\"startUtcOffset\\\": \\\"0s\\\",\\n \\\"endTime\\\": \\\"2026-03-03T20:59:30Z\\\",\\n \\\"endUtcOffset\\\": \\\"0s\\\",\\n \\\"type\\\": \\\"AWAKE\\\",\\n \\\"createTime\\\": \\\"2026-03-04T04:43:40.937183Z\\\",\\n \\\"updateTime\\\": \\\"2026-03-04T04:43:40.937183Z\\\"\\n },\\n[...]\\n### Aggregate data points over a range of time\\n[...]\\nUse the `rollUp`\\nendpoint to return the\\naggregate of data points based on a window in seconds, over the `datetime` range\\nbased on the users physical time (in UTC).\\n[...]\\n### Aggregate data across a single day or multiple days\\n[...]\\nThe `dailyRollUp`\\nendpoint should be\\nused when you want to aggregate data across\\na single day or multiple days, known as `windowSize`. Provide the closed-open\\ncivil time range for the required interval in the request body. Depending on the\\ndata type, you will either receive the sum or the average over the interval.\\n[...]\\n### Insert or update a user's health data\",\n \"position\": 3\n },\n {\n \"url\": \"https://developers.google.com/fit/datatypes/activity\",\n \"title\": \"Activity data types  |  Google Fit  |  Google for Developers\",\n \"description\": \"# Activity data types\\n[...]\\nThis data type can be used to capture any activity a user does. This can be\\ncommon fitness activities like running or different sports, as well as\\nactivities like meditation, gardening, and sleep.\\n[...]\\n|---|---|\\n| Name | `com.google.activity.segment` |\\n| OAuth permission scopes | https://www.googleapis.com/auth/fitness.activity.read https://www.googleapis.com/auth/fitness.activity.write |\\n| Fields (format---units) | activity type (`int`---enum) The type of activity the user was doing. See the list of activity types here. |\\n[...]\\n## Basal metabolic rate (BMR)\\n[...]\\nThis data type captures the BMR of a user, in kilocalories. Each data point\\nrepresents The number of kilocalories a user would burn if at rest all day,\\nbased on their height and weight. Only the end time should be set. This\\nwill be used as the timestamp for the reading.\\n[...]\\n## Heart Points\\n[...]\\nThis data type captures the number of Heart Points a user has earned, from all\\ntheir activity. Each data point represents the number of Heart Points calculated\\nfor a time interval.\\n[...]\\nUser's can set a daily Heart Point goal and track their progress. Heart Points\\ncan be calculated using:\\n[...]\\n- heart rate\\n- Metabolic Equivalent of Task (MET) values\\n- walking speed\\n[...]\\nThe number of Heart Points earned depends on the intensity of the activity. Use\\nthis guide to calculate and write Heart Points:\\n[...]\\n| Data | 1 HP (Low-medium intensity activity) | 2 HPs (High intensity activity) |\\n| --- | --- | --- |\\n| Heart rate | 1 minute of actvity at >50% maximum heart rate | 1 minute of activity at >70% max heart rate |\\n| MET value | 3-6 MET. For example, rowing or rock climbing, | >6 MET. For example, HIIT, skiing, volleyball or football. |\\n| Walking speed | 100-130 steps per minute | >130 steps per minute |\\n[...]\\n|---|---|\\n| Name | `com.google.heart_minutes` |\\n| OAuth permission scopes | https://www.googleapis.com/auth/fitness.activity.read https://www.googleapis.com/auth/fitness.activity.write |\\n| Fields (format---units) | intensity (`float`---Heart Points) Heart Points earned based on the intensity of the exercise or activity the user does. |\\n[...]\\n|---|---|\\n[...]\\n| Name | `com.google.heart_minutes` |\\n| Data type object | `TYPE_HEART_MINUTES` |\\n| Fields (format---units) | FIELD_INTENSITY (`float`---heart points) The intensity of the exercise or activity the user does. One minute of light to moderate physical activity (like walking faster than 2.5 mph, or cycling faster than 10 mph) earns 1 heart point. One minute of more intense activity earns 2 heart points. |\\n[...]\\n## Move Minutes\\n[...]\\nThis data type captures the number\\n[...]\\n. Each data point represents the\\n[...]\\n## Step count cadence\\n[...]\\nThis data type captures the walking cadence, measured in steps per minute. Each\\ndata point represents an instantaneous measurement of the cadence in steps per\\nminute.\\n[...]\\n) | rpm (`float`---steps/minute) Cadence measured in steps per minute. |\\n[...]\\n## Step count delta\\n[...]\\nThis data type captures the number of steps taken since the last reading. Each\\nstep is only reported once so data points shouldn't have overlapping time. The\\nstart time of each data point should represent the start of the interval in\\nwhich steps were taken.\\n[...]\\n|---|---|\\n| Name | `com.google.step_count.delta` |\\n| OAuth permission scopes | https://www.googleapis.com/auth/fitness.activity.read https://www.googleapis.com/auth/fitness.activity.write |\\n| Fields (format---units) | |---| | steps (`int`---count) Number of steps taken over a time period. Valid range: 0---10 steps per second | |\",\n \"position\": 4\n },\n {\n \"url\": \"https://developers.google.com/fit/datatypes/nutrition\",\n \"title\": \"Nutrition data types  |  Google Fit  |  Google for Developers\",\n \"description\": \"# Nutrition data types\\n[...]\\nData types for nutrition data.\\n[...]\\nEach data point represents what nutrients were consumed as part of a meal\\nor a food item. The data point contains several fields. The nutrients field is\\nrequired. And either one, or both, of the meal type and food item fields are required.\\n[...]\\n> [!NOTE]\\n> Note: If exact meal times are known, add these specific start and end times. If not, add the start and end times of the general time range the meal was eaten.\\n[...]\\n|---|---|\\n| Name | `com.google.nutrition` |\\n| OAuth permission scopes | https://www.googleapis.com/auth/fitness.nutrition.read https://www.googleapis.com/auth/fitness.nutrition.write |\\n[...]\\n| Fields (format---units) | |---| | meal type (`int`---enum) (optional field) What kind of meal the user ate. Accepted values\\n[...]\\n`restructuredtext \\\"intVal\\\": 1 // Unknown \\\"intVal\\\": 2 // Breakfast \\\"intVal\\\": 3 // Lunch \\\"intVal\\\": 4 // Dinner \\\"intVal\\\": 5 // Snack ` | | food item (`string`---n/a) The specific food item for the entry. For example, \\\"banana\\\" or \\\"porridge\\\". | | nutrients (`Map`---calories/grams) The nutritional breakdown of the food item eaten. Accepted values `restructuredtext \\\"key\\\": \\\"calories\\\" // Calories in kcal \\\"key\\\": \\\"fat.total\\\" // Total fat in grams \\\"key\\\": \\\"fat.saturated\\\" // Saturated fat in grams \\\"key\\\": \\\"fat.unsaturated\\\" // Unsaturated fat in grams \\\"key\\\": \\\"fat.polyunsaturated\\\" // Polyunsaturated fat in grams \\\"key\\\": \\\"fat.monounsaturated\\\" // Monounsaturated fat in grams \\\"key\\\": \\\"fat.trans\\\" // Trans fat in grams \\\"key\\\": \\\"cholesterol\\\" // Cholesterol in milligrams \\\"key\\\": \\\"sodium\\\" // Sodium in milligrams \\\"key\\\": \\\"potassium\\\" // Potassium in milligrams \\\"key\\\": \\\"carbs.total\\\" // Total carbohydrates in grams \\\"key\\\": \\\"dietary_fiber\\\" // Dietary fiber in grams \\\"key\\\": \\\"sugar\\\" // Amount of sugar in grams \\\"key\\\": \\\"protein\\\" // Protein amount in grams ` | |\\n[...]\\n|---|---|\\n| Name | `com.google.nutrition` |\\n| Data type object | `TYPE_NUTRITION` |\\n[...]\\n| Fields (format---units) | |---| | FIELD_MEAL_TYPE (`int`---enum) (optional field) What kind of meal the user ate. Accepted values\\n[...]\\n`MEAL_TYPE_UNKNOWN // Unknown MEAL_TYPE_BREAKFAST // Breakfast MEAL_TYPE_LUNCH // Lunch MEAL_TYPE_DINNER // Dinner MEAL_TYPE_SNACK // Snack` | | FIELD_FOOD_ITEM (`string`---free-form text) A description of the food for the entry. For example, \\\"banana\\\" or \\\"porridge\\\". | | FIELD_NUTRIENTS (`Map`---kilocalories/grams/milligrams) The nutritional breakdown of the food item eaten. Accepted values `NUTRIENT_CALORIES // Calories in kcal NUTRIENT_TOTAL_FAT // Total fat in grams NUTRIENT_SATURATED_FAT // Saturated fat in grams NUTRIENT_UNSATURATED_FAT // Unsaturated fat in grams NUTRIENT_POLYUNSATURATED_FAT // Polyunsaturated fat in grams NUTRIENT_MONOUNSATURATED_FAT // Monounsaturated fat in grams NUTRIENT_TRANS_FAT // Trans fat in grams NUTRIENT_CHOLESTEROL // Cholesterol in milligrams NUTRIENT_SODIUM // Sodium in milligrams NUTRIENT_POTASSIUM // Potassium in milligrams NUTRIENT_TOTAL_CARBS // Total carbohydrates in grams NUTRIENT_DIETARY_FIBER // Dietary fiber in grams NUTRIENT_SUGAR // Amount of sugar in grams NUTRIENT_PROTEIN // Protein amount in grams` | |\",\n \"position\": 5\n }\n ]\n }\n}", "tool_call_id": "call_00_oGVGnEVqryiKV43jtQXd5191" } ] }