Strava MCP Server

Strava MCP Server

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Strava MCP Server

A Model Context Protocol (MCP) server that provides access to the Strava API. This server enables language models to interact with Strava data, including activities, athlete information, and more.

Features

  • 🏃‍♂️ Activity tracking and analysis
  • 📊 Athlete statistics
  • 🗺️ Route visualization
  • 🏆 Achievement tracking
  • 🤝 Social features (kudos, comments)

Prerequisites

  • Python 3.12+
  • Strava API credentials
  • pip (Python package installer)

Installation

  1. Clone the repository:
git clone https://github.com/yourusername/strava_mcp.git
cd strava_mcp
  1. Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt

Configuration

  1. Create a config/.env file with your Strava API credentials:
STRAVA_CLIENT_ID=your_client_id
STRAVA_CLIENT_SECRET=your_client_secret
STRAVA_REFRESH_TOKEN=your_refresh_token
  1. To obtain Strava API credentials:
    • Go to https://www.strava.com/settings/api
    • Create a new application
    • Note down the Client ID and Client Secret
    • Follow the OAuth 2.0 flow to get your refresh token

Usage

Using with Claude

Once connected, you can interact with your Strava data through Claude in various ways:

Activity Queries

  • "Show me my recent activities"
  • "Get details about my last run"
  • "What was my longest ride this month?"
  • "Show me activities where I set personal records"
  • "Display the route map for my latest activity"

Performance Analysis

  • "What's my average running pace this year?"
  • "Compare my cycling performance between last month and this month"
  • "Show me my heart rate zones from yesterday's workout"
  • "What's my total elevation gain for all activities?"
  • "Calculate my weekly mileage for running"

Social Interactions

  • "Who gave kudos on my latest activity?"
  • "Show me comments on my marathon run"
  • "List all my club activities"
  • "Find activities I did with friends"

Achievement Tracking

  • "List all my segment achievements"
  • "Show my personal records on local segments"
  • "What achievements did I earn this week?"
  • "Display my progress on yearly goals"

Data Available Through Claude

  1. Activity Details:

    • Distance, duration, pace
    • Route maps and elevation profiles
    • Heart rate, power, and cadence data
    • Splits and lap information
    • Weather conditions during activity
  2. Athlete Statistics:

    • Year-to-date and all-time totals
    • Personal records and achievements
    • Training load and fitness trends
    • Equipment usage and maintenance
  3. Social Data:

    • Kudos and comments
    • Club activities and leaderboards
    • Friend activities and challenges
    • Segment efforts and rankings
  4. Route Information:

    • Detailed maps with elevation data
    • Segment analysis
    • Popular routes and segments
    • Route planning and analysis

As an MCP Server

Update your Claude Desktop configuration:

{
    "mcpServers": {
        "Strava": {
            "command": "python",
            "args": ["src/strava_server.py"],
            "cwd": "/path/to/strava_mcp",
            "env": {
                "STRAVA_CLIENT_ID": "your_client_id",
                "STRAVA_CLIENT_SECRET": "your_client_secret",
                "STRAVA_REFRESH_TOKEN": "your_refresh_token"
            }
        }
    }
}

As an HTTP Server

  1. Start the server:
./run_server.sh
  1. Access the API at http://localhost:8000

Available endpoints:

  • GET /activities/recent - List recent activities
  • GET /activities/{id} - Get activity details
  • GET /activities/{id}/map - Get activity map visualization
  • GET /athlete/stats - Get athlete statistics

Development

Project Structure

strava_mcp/
├── src/
│   ├── strava_server.py      # MCP server implementation
│   ├── strava_http_server.py # HTTP API server
│   ├── map_utils.py          # Map visualization utilities
│   └── templates.py          # HTML templates
├── config/
│   └── .env                  # Environment variables (not in git)
├── requirements.txt          # Python dependencies
└── run_server.sh            # Server startup script

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

Security

  • Never commit .env files or API credentials
  • The .gitignore file is configured to prevent sensitive data from being committed
  • Use environment variables for all sensitive configuration

License

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

Acknowledgments

  • Strava API Documentation
  • Model Context Protocol (MCP) Specification
  • Contributors and maintainers

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