Strava

🚀 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, etc.

✨ Features

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

📦 Installation

Prerequisites

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

Steps

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

Set up the .env file

1. Create a config/.env file and enter your Strava API credentials:

STRAVA_CLIENT_ID=your_client_id
STRAVA_CLIENT_SECRET=your_client_secret
STRAVA_REFRESH_TOKEN=your_refresh_token

Obtain Strava API credentials

• Visit https://www.strava.com/settings/api
• Create a new application
• Note down your client ID and client secret
• Follow the OAuth 2.0 flow to obtain a refresh token

💻 Usage Examples

Using with Claude

After connecting, you can interact with your Strava data in various ways through Claude:

Activity Queries

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

Performance Analysis

• "What's my average running pace this year?"
• "During which time periods did I exercise most frequently in the past week?"
• "What's my maximum heart rate?"
• "What's my average heart rate?"
• "How many calories did I burn?"

Data Visualization

• "Draw a map of my recent activities"
• "Generate a chart of my running distances in the past month"
• "Show my heart rate distribution diagram"
• "Display my pace change trend"
• "Draw my elevation profile"

Social Interaction

• "Recommend some athletes at my level"
• "Share my activity on social media"
• "Get the recent activity updates of my friends"
• "Compare my running data with my friends'"
• "Analyze my ranking in the community"

Other Features

Activity Calendar

• "Show my planned activities for the next two weeks"
• "Generate a chronology of my activities in the past year"
• "Count my activity frequency by month"
• "Mark all my completed activities"
• "Remind me of upcoming important races"

Health Analysis

• "Evaluate my Training Load Index (TLI)"
• "Calculate my Rating of Perceived Exertion (RPE)"
• "Provide data-based training suggestions"
• "Analyze my fatigue state"
• "Recommend appropriate rest and recovery plans"

Data Export

• "Export my data from the past year as a CSV file"
• "Generate a report suitable for Excel analysis"
• "Download the GPX file of my activity tracks"
• "Output detailed logs of heart rate and pace"
• "Save all photos to a local folder"

🔧 Technical Details

Project Structure

1. Main Directory
   • strava_mcp_server.py: Main server script
   • config/: Configuration files and environment variables
   • models/: Model and algorithm implementations
   • data/: Data storage and processing
   • api/: API interface definitions and routes

Contribution Guidelines

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

⚠️ Important Note

• Prevent data leakage:

  • Do not commit the .env file or other files containing sensitive information to the version control system.
  • Use environment variables to manage all sensitive configurations and avoid hard - coding.

• Code security:

  • Input validation: Conduct strict checks and filtering on user input to prevent injection attacks.
  • Authentication and authorization: Implement multi - level authentication mechanisms to ensure that only authorized users can access sensitive data.
  • Data encryption: Encrypt sensitive information during transmission and storage, and use HTTPS for communication.

• Logging:

  • Record detailed error logs and operation logs to detect abnormal behavior in a timely manner.
  • Regularly review log files to monitor potential security threats.

• Regular audits:

  • Conduct regular security audits on the code to identify potential vulnerabilities.
  • Keep an eye on the latest security announcements and fix known vulnerabilities in a timely manner.

📄 License

This project is licensed under the MIT License. For more details, please refer to the LICENSE file.

🙏 Acknowledgments

• Strava API documentation
• Model Context Protocol (MCP) specification
• Contributors and maintainers