Интеграция Strava API с Model Context Protocol (MCP) SDK

What is Интеграция Strava API с Model Context Protocol (MCP) SDK?

An MCP server that connects Strava data to AI assistants via the Model Context Protocol. It analyzes workouts, provides training recommendations, and manages Strava API authentication automatically.

How to use Интеграция Strava API с Model Context Protocol (MCP) SDK?

Install Python 3.10+, clone the repository, and use uv to install dependencies. Configure a Strava API application, create a .env file from the template, run python scripts/auth.py to obtain tokens, then launch with mcp dev src/server.py.

Key features of Интеграция Strava API с Model Context Protocol (MCP) SDK

• Read resources: activities, zones, clubs, gear
• Tools: analyze_activity, analyze_training_load, get_activity_recommendations
• Automatic token refresh for Strava API
• Rate limiting (100 requests per 15 minutes)
• Built with MCP Python SDK
• MIT licensed, open source

Use cases of Интеграция Strava API с Model Context Protocol (MCP) SDK

• Analyze a single run or ride to get pace, effort, and heart rate insights
• Monitor total training load across multiple activities over time
• Retrieve current heart rate and power zones for targeted workouts
• Get personalized workout recommendations based on recent activity history
• View detailed gear information used in Strava activities

FAQ from Интеграция Strava API с Model Context Protocol (MCP) SDK

What software is required?

Python 3.10+, Claude Desktop, a Strava account, and the uv package manager (recommended).

How do I obtain Strava API tokens?

Run python scripts/auth.py after setting up your Strava API application and filling the required client ID, client secret, and callback domain in the .env file.

Is there a rate limit?

Yes, the server enforces a rate limit of 100 API requests per 15 minutes to comply with Strava’s limits.

What resources and tools are exposed?

Resources: strava://activities, strava://activities/{id}, strava://athlete/zones, strava://athlete/clubs, strava://gear/{gear_id}. Tools: analyze_activity, analyze_training_load, get_activity_recommendations.

Is this server open source?

Yes, it is released under the MIT license and contributions are welcome via GitHub pull requests.