Fitbit MCP Connector for AI

> 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?

Option 1: Install from npm (Recommended)

1. Get Fitbit API credentials

2. Install the package globally:

npm install -g mcp-fitbit

3. 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"
      }
    }
  }
}

4. Restart Claude Desktop and ask about your Fitbit data!

Option 2: Development Setup

1. Get Fitbit API credentials (see Installation below)

2. 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)

1. Get Fitbit API credentials at dev.fitbit.com

2. Install the package:

npm install -g mcp-fitbit

3. 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

4. Add your credentials to the `.env` file:

FITBIT_CLIENT_ID=your_client_id_here
   FITBIT_CLIENT_SECRET=your_client_secret_here

5. Run the server:

mcp-fitbit

For Developers (from source)

1. Get Fitbit API credentials at dev.fitbit.com

2. Clone and setup:

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

3. Create `.env` file:

FITBIT_CLIENT_ID=your_client_id_here
   FITBIT_CLIENT_SECRET=your_client_secret_here

4. Build the server:

npm run build

Available Tools

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:

1. The server opens your browser to `http://localhost:3000/auth`

2. Log in to Fitbit and grant permissions

3. You'll be redirected to a success page

4. 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.