Fitbit MCP Connector for AI

Connect AI assistants to your Fitbit health data (includes heart rate variability - HRV)

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, zones and variability
🍎 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?

Option 1: Install from npm (Recommended)

Get Fitbit API credentials
- Create an app with OAuth 2.0 Application Type: Personal
- Set Callback URL: http://localhost:3000/callback
- Note your Client ID and Client Secret
Install the package globally:

npm install -g mcp-fitbit

Add to your Claude Desktop config file:

{
  "mcpServers": {
    "fitbit": {
      "command": "mcp-fitbit",
      "args": [],
      "env": {
        "FITBIT_CLIENT_ID": "your_client_id_here",
        "FITBIT_CLIENT_SECRET": "your_client_secret_here"
      }
    }
  }
}

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

Restart Claude Desktop and ask about your Fitbit data!

Option 2: Development Setup

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

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

Installation

For End Users (npm package)

Get Fitbit API credentials at dev.fitbit.com
- Set OAuth 2.0 Application Type to Personal
- Set Callback URL to http://localhost:3000/callback
Install the package:
```
npm install -g mcp-fitbit
```
Create .env file in the package directory:

When you run mcp-fitbit for the first time, it will tell you exactly where to create the .env file. It will look something like:
```
C:\Users\YourName\AppData\Roaming\npm\node_modules\mcp-fitbit\.env
```

Add your credentials to the .env file:

FITBIT_CLIENT_ID=your_client_id_here
FITBIT_CLIENT_SECRET=your_client_secret_here

Run the server:
```
mcp-fitbit
```

For Developers (from source)

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

Clone and setup:

git clone https://github.com/TheDigitalNinja/mcp-fitbit
cd mcp-fitbit
npm install

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
`get_hrv`	Daily RMSSD and deep sleep RMSSD (HRV)	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

Using npm package (recommended):

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "fitbit": {
      "command": "mcp-fitbit",
      "args": []
    }
  }
}

Using local development version:

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 TASKS.md for improvement opportunities and technical details.

@einlogic/mcp-fitbit

Quick Install