TrainingPeaks MCP Server

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Connect TrainingPeaks to Claude and other AI assistants via the Model Context Protocol (MCP). Query workouts, build structured intervals, track fitness trends, and write comments/feedback on your calendar through natural conversation.

No more expired cookies. This server features automatic login using your TrainingPeaks username and password. The credentials remain local on your machine and are only transmitted directly to TrainingPeaks over secure HTTPS.

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What You Can Do

Ask your AI assistant things like:

• "Build me a 4x8min threshold session for Tuesday with warm-up and cool-down"
• "Show my workouts for this week and check if I've completed them"
• "Analyze my compliance for yesterday's run and add a feedback comment in TrainingPeaks"
• "What's my CTL, ATL, and TSB trend for the last 90 days?"
• "Get my profile and account type"

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Tools (8)

Workouts & Intervals

• tp_get_workouts: List planned and completed workouts in a date range (max 90 days).
• tp_create_workout: Create planned workouts on a calendar date (supports complex nested interval structures, auto-computed TSS/IF, and planned start times).
• tp_delete_workout: Delete planned workouts by ID.

Comments & Feedback

• tp_get_workout_comments: Fetch the list of comments from a workout.
• tp_add_workout_comment: Add a text comment (e.g. analysis, compliance review) to a workout.

Performance & Summary

• tp_get_profile: Get athlete profile info (Athlete ID, Name, Email, Premium/Basic account status).
• tp_get_weekly_summary: Aggregate view of workouts, total TSS, total duration, and end-of-week fitness.
• tp_get_fitness: Fetch CTL (Fitness), ATL (Fatigue), and TSB (Form) performance metrics.

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Setup in Claude Desktop

Add the server to your claude_desktop_config.json:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "trainingpeaks": {
      "command": "python",
      "args": [
        "-m",
        "tp_mcp",
        "serve"
      ],
      "env": {
        "TP_USERNAME": "YOUR_TRAININGPEAKS_USERNAME",
        "TP_PASSWORD": "YOUR_TRAININGPEAKS_PASSWORD"
      }
    }
  }
}

[!NOTE] Ensure you run this inside the virtual environment where tp-mcp is installed, or point the "command" path directly to the python.exe/python binary of the virtual environment.

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Security & Privacy

This server is designed to be completely secure and private:

1. 100% Local: Runs on your local machine. No external databases, no middleware, no credential sharing.
2. Direct Connection: Authenticates directly with TrainingPeaks official servers using HTTPS.
3. No exposed ports: Uses standard input/output (stdio) to communicate with Claude Desktop. It does not open any network ports.

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Development & Testing

To set up the project locally and run the tests:

# Clone the repository
git clone https://github.com/tildecomunicacion/trainingpeaks_mcp.git
cd trainingpeaks-mcp

# Create a virtual environment and install dependencies
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -e ".[dev]"

# Run unit tests
pytest

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License

MIT