Coach MCP server

coach-mcp

<!-- mcp-name: io.github.snoozelieb/coach-mcp -->

An opinionated AI training coach as an MCP server. It pulls your real data from Garmin Connect and prescribes with authority — science-based load management (ACWR), code-enforced injury gates (the server rejects plans that violate an active injury restriction, no matter what the LLM says), and persistent coaching memory so decisions, rationale, and your adaptation patterns survive between conversations. It will tell you "no" when your enthusiasm exceeds your capacity.

All health data and credentials stay on your machine — see Security & Privacy.

Quickstart

You need Python 3.12+, a free Garmin Connect account, and an MCP client (Claude Code, Claude Desktop, or Cursor).

Option A: uvx (recommended)

No install step — your MCP client runs the server on demand:

uvx garmin-coach-mcp

Jump to Connect your MCP client and use uvx as the command.

Option B: from source

git clone https://github.com/snoozelieb/coach-mcp.git
cd coach-mcp

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

pip install -r requirements.txt
cp .env.example .env   # then edit: GARMIN_EMAIL, GARMIN_PASSWORD
python server.py

Connect your MCP client

The server needs two environment variables: GARMINEMAIL and GARMINPASSWORD. Optional: COACHDATADIR (where your coaching data lives) and ANTHROPICAPIKEY (only for the standalone daily_loop.py --llm script). From a source checkout, a .env file works too.

Claude Code

claude mcp add coach-mcp \
  --env GARMIN_EMAIL=you@example.com \
  --env GARMIN_PASSWORD=your_garmin_password \
  -- uvx garmin-coach-mcp

Or in .mcp.json:

{
  "mcpServers": {
    "coach-mcp": {
      "command": "uvx",
      "args": ["garmin-coach-mcp"],
      "env": {
        "GARMIN_EMAIL": "you@example.com",
        "GARMIN_PASSWORD": "your_garmin_password",
        "COACH_DATA_DIR": "/path/to/your/coach-data"
      }
    }
  }
}

Running from source instead: claude mcp add coach-mcp -- python /full/path/to/coach-mcp/server.py

Claude Desktop

In claudedesktopconfig.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "coach-mcp": {
      "command": "uvx",
      "args": ["garmin-coach-mcp"],
      "env": {
        "GARMIN_EMAIL": "you@example.com",
        "GARMIN_PASSWORD": "your_garmin_password",
        "COACH_DATA_DIR": "/path/to/your/coach-data"
      }
    }
  }
}

Cursor

In .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
  "mcpServers": {
    "coach-mcp": {
      "command": "uvx",
      "args": ["garmin-coach-mcp"],
      "env": {
        "GARMIN_EMAIL": "you@example.com",
        "GARMIN_PASSWORD": "your_garmin_password",
        "COACH_DATA_DIR": "/path/to/your/coach-data"
      }
    }
  }
}

If you installed with pip install garmin-coach-mcp instead of uvx, use "command": "garmin-coach-mcp" with no args in any of the blocks above.

First run

1. Create your profile. From a source checkout, run the interactive wizard:

python scripts/setup_wizard.py

It creates your athlete profile, training config, and empty plan/memory files in the data directory. Alternatively, create the two required files by hand and let the coach fill in the rest via conversation:

echo '{"personal":{"name":null},"injury_history":[],"life_constraints":{}}' > data/athlete.json
   echo '{"events":[],"current_block":{"phase":"base"}}' > data/training_config.json

1. Pull your Garmin baseline. In your MCP client, say:

Shortened. The full README is on GitHub.