MCPInstall
Strava logo

Strava

by ctvidic 6 stars ctvidic/strava-mcp-server

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

READMEmain

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:

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

More Research & Data MCP servers

Similar servers from the same category.

WeatherXM PRO

weatherxm

Integrates with WeatherXM PRO APIs to provide access to hyperlocal weather data, historical observations, and forecast performance metrics for location-specific analysis and planning.

APICLI+6

Gralio

tymonte

Access 3+ million SaaS reviews, detailed pricing data, alternatives, ratings, funding information, growth metrics, user sentiment analysis, and functional feature data for over 30,000 software products.

Research & Data

Integrates with professional cryptocurrency data APIs from DefiLlama Pro, CoinGecko Pro, and Arkham Intelligence to provide real-time token prices, market data, blockchain analytics, and on-chain intelligence for crypto researchers and traders.

search

Enables semantic and keyword searches across Space Frontiers' library, telegram, and reddit databases through a FastAPI-based server with flexible authentication options.

databaseauthentication+1