Strava

Integrates with the Strava API to enable access to fitness tracking data and activity information for analyzing workout patterns and athletic performance.

Installation Instructions

README: https://github.com/ctvidic/strava-mcp-server

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

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate

3. 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

2. 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

2. 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