README - Fitbit MCP Server by thedigitalninja

Fitbit MCP Server

Connect AI assistants to your Fitbit health data

Give your AI assistant access to your Fitbit data for personalized health insights, trend analysis, and automated tracking. Works with Claude Desktop and other MCP-compatible AI tools.

What it does

🏃 Exercise & Activities - Get detailed workout logs and activity data
😴 Sleep Analysis - Retrieve sleep patterns and quality metrics
⚖️ Weight Tracking - Access weight trends over time
❤️ Heart Rate Data - Monitor heart rate patterns and zones
🍎 Nutrition Logs - Review food intake, calories, and macros
👤 Profile Info - Access basic Fitbit profile details

Ask your AI things like: "Show me my sleep patterns this week" or "What's my average heart rate during workouts?"

Quick Start

🚀 Want to test the tools right away?

Get Fitbit API credentials (see Installation below)
Then run:

git clone https://github.com/TheDigitalNinja/mcp-fitbit
cd mcp-fitbit
npm install
# Create .env with your Fitbit credentials
npm run dev

This opens the MCP Inspector at http://localhost:5173 where you can test all tools interactively and handle the OAuth flow.

Installation

Get Fitbit API credentials at dev.fitbit.com
- Set OAuth 2.0 Application Type to Personal
- Set Callback URL to http://localhost:3000/callback

Create .env file:

FITBIT_CLIENT_ID=your_client_id_here
FITBIT_CLIENT_SECRET=your_client_secret_here

Build the server:
```
npm run build
```

Available Tools

Tool	Description	Parameters
`get_weight`	Weight data over time periods	`period`: `1d`, `7d`, `30d`, `3m`, `6m`, `1y`
`get_sleep_by_date_range`	Sleep logs for date range (max 100 days)	`startDate`, `endDate` (YYYY-MM-DD)
`get_exercises`	Activity/exercise logs after date	`afterDate` (YYYY-MM-DD), `limit` (1-100)
`get_daily_activity_summary`	Daily activity summary with goals	`date` (YYYY-MM-DD)
`get_activity_goals`	User's activity goals (daily/weekly)	`period`: `daily`, `weekly`
`get_activity_timeseries`	Activity time series data (max 30 days)	`resourcePath`, `startDate`, `endDate` (YYYY-MM-DD)
`get_azm_timeseries`	Active Zone Minutes time series (max 1095 days)	`startDate`, `endDate` (YYYY-MM-DD)
`get_heart_rate`	Heart rate for time period	`period`: `1d`, `7d`, `30d`, `1w`, `1m`, optional `date`
`get_heart_rate_by_date_range`	Heart rate for date range (max 1 year)	`startDate`, `endDate` (YYYY-MM-DD)
`get_food_log`	Complete nutrition data for a day	`date` (YYYY-MM-DD or "today")
`get_nutrition`	Individual nutrient over time	`resource`, `period`, optional `date`
`get_nutrition_by_date_range`	Individual nutrient for date range	`resource`, `startDate`, `endDate`
`get_profile`	User profile information	None

Nutrition resources: caloriesIn, water, protein, carbs, fat, fiber, sodium

Activity time series resources: steps, distance, calories, activityCalories, caloriesBMR, tracker/activityCalories, tracker/calories, tracker/distance

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "fitbit": {
      "command": "node",
      "args": ["C:\\path\\to\\mcp-fitbit\\build\\index.js"]
    }
  }
}

Config file locations:

Windows: %AppData%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

First Run Authorization

When you first ask your AI assistant to use Fitbit data:

The server opens your browser to http://localhost:3000/auth
Log in to Fitbit and grant permissions
You'll be redirected to a success page
Your AI can now access your Fitbit data!

Development

npm run lint          # Check code quality
npm run format        # Fix formatting
npm run build         # Compile TypeScript
npm run dev           # Run with MCP inspector

Architecture: See for improvement opportunities and technical details.