Garmin MCP Server

Garmin MCP Server

Enables AI assistants to access Garmin Connect fitness and health data, including activities, heart rate, sleep, and device information.

Category
Visit Server

README

Garmin MCP (Model Context Protocol) Server

A Model Context Protocol server that provides seamless integration with Garmin Connect, allowing AI assistants to access your Garmin fitness and health data.

Features

  • Activity Data: Access recent activities, detailed workout information
  • Health Metrics: Retrieve heart rate, sleep, and stress data
  • Daily Statistics: Get daily activity summaries and statistics
  • Device Information: Query connected Garmin device details
  • Date Range Queries: Fetch historical data for specific time periods

Prerequisites

  • Python 3.8 or higher
  • A Garmin Connect account
  • MCP-compatible AI assistant (Claude Desktop, etc.)

Installation

  1. Clone this repository:
git clone https://github.com/hsavelli/Garmin-MCP.git
cd Garmin-MCP
  1. Install dependencies:
pip install garminconnect mcp

Note: in some instances you might need to use the command pip3 instead.

Configuration

For Claude Desktop

Add the following to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "garmin": {
      "command": "python", 
      "args": ["/path/to/garmin_mcp.py"]
    }
  }
}

Note: in some instances you might need to use the command python3 instead.

Usage

Once configured, the MCP server provides the following capabilities:

Resources

The server exposes these Garmin data resources:

  • garmin://activities/recent - Recent activities list
  • garmin://stats/daily - Today's statistics
  • garmin://health/heart-rate - Heart rate data
  • garmin://health/sleep - Sleep tracking data
  • garmin://health/stress - Stress level measurements
  • garmin://device/info - Connected device information

Tools

Available tools for interacting with Garmin Connect:

  1. authenticate_garmin - Authenticate with your Garmin Connect account

    • Parameters: email, password
  2. get_activity_details - Get detailed information about a specific activity

    • Parameters: activity_id
  3. get_stats_range - Get statistics for a date range

    • Parameters: start_date, end_date (format: YYYY-MM-DD)
  4. sync_device - Trigger device sync with Garmin Connect

Example Interactions

In your AI assistant, you can:

"Authenticate with my Garmin account using email@example.com"
"Show me my recent activities"
"What was my heart rate data today?"
"Get my sleep data from last night"
"Show me my activity statistics for the past week"

Security Notes

  • Credentials are never stored by the MCP server
  • Authentication is required for each session
  • All data is fetched directly from Garmin Connect API
  • No data is cached or persisted locally

Development

Project Structure

garmin_mcp.py    # Main MCP server implementation
README.md        # This file

Adding New Features

To add new Garmin data endpoints:

  1. Add a new resource in list_resources()
  2. Implement the data fetching logic in read_resource()
  3. Create a helper method for the specific data type
  4. Optionally add a new tool in list_tools() for advanced functionality

Troubleshooting

Authentication Issues

  • Ensure your Garmin Connect credentials are correct
  • Check if you have 2FA enabled (may require app-specific password)
  • Verify your account isn't locked due to too many attempts

Connection Errors

  • Check your internet connection
  • Garmin Connect may be temporarily unavailable
  • Rate limiting may apply for excessive requests

MCP Connection Issues

  • Verify the path to garmin_mcp.py in your configuration
  • Ensure Python is in your system PATH
  • Check MCP server logs for detailed error messages

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

This project is not affiliated with, endorsed by, or sponsored by Garmin Ltd. or its subsidiaries. It uses the unofficial garminconnect Python library to interact with Garmin Connect services.

Acknowledgments

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured