Gym Coach MCP Server

Gym Coach MCP Server

Connects to a Gym Tracker Supabase database to provide LLMs with access to personal workout history, routines, and training progress. It enables users to analyze fitness performance, track personal records, and receive personalized coaching advice through natural language.

Category
访问服务器

README

Gym Coach MCP Server

MCP server that turns any compatible LLM into a personal gym coach with access to your real workout data from Gym Tracker.

Built on the Model Context Protocol — works with Claude Desktop, Claude Code, Cursor, Continue, Cline, and any MCP-compatible client.

What it does

The server connects to your Gym Tracker Supabase database and exposes your training data through 5 tools and 1 resource:

Tools

Tool Description Parameters
get_workout_history Recent workouts with exercises, weights, and reps limit, from_date, to_date
get_exercise_progress Progression history for a specific exercise (max weight, volume, trends) exercise_name, limit
get_routines All routines with exercises, sets, reps, and muscle groups
get_training_plan Active training plan with progress and completion percentage
get_stats_summary KPIs: total workouts, frequency, top exercises, PRs period_days

Resources

Resource Description
gym://exercise-catalog Complete exercise catalog with muscle groups and equipment

Example prompts

  • "How's my bench press progress looking?"
  • "Am I training enough leg volume compared to upper body?"
  • "Give me a summary of my last month"
  • "Am I on track with my training plan?"
  • "When was my last PR on squats?"
  • "Suggest improvements to my push routine"

Setup

1. Install dependencies

cd gym-tracker-mcp
npm install

2. Configure environment

Copy .env.example to .env and fill in your credentials:

cp .env.example .env
SUPABASE_URL=https://your-project.supabase.co
SUPABASE_ANON_KEY=eyJ...
GYM_EMAIL=your@email.com
GYM_PASSWORD=your-password

Uses your existing Gym Tracker account credentials. All queries go through Supabase RLS — you can only access your own data.

3. Build

npm run build

4. Connect to your LLM client

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "gym-coach": {
      "type": "stdio",
      "command": "node",
      "args": ["/absolute/path/to/gym-tracker-mcp/dist/index.js"]
    }
  }
}

Claude Code

Add to .mcp.json in your project root or ~/.claude.json globally:

{
  "mcpServers": {
    "gym-coach": {
      "type": "stdio",
      "command": "node",
      "args": ["/absolute/path/to/gym-tracker-mcp/dist/index.js"]
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "gym-coach": {
      "type": "stdio",
      "command": "node",
      "args": ["/absolute/path/to/gym-tracker-mcp/dist/index.js"]
    }
  }
}

Continue (VS Code / JetBrains)

Add to ~/.continue/config.json:

{
  "mcpServers": [
    {
      "name": "gym-coach",
      "command": "node",
      "args": ["/absolute/path/to/gym-tracker-mcp/dist/index.js"]
    }
  ]
}

Replace /absolute/path/to/ with the actual path to your gym-tracker-mcp directory.

Development

npm run dev    # Watch mode with tsx (hot reload)
npm run build  # Compile TypeScript to dist/
npm start      # Run compiled server

Architecture

gym-tracker-mcp/
├── src/
│   └── index.ts      # MCP server (~450 lines)
├── dist/              # Compiled JS (after npm run build)
├── .env               # Your credentials (not committed)
├── .env.example       # Template
├── package.json
└── tsconfig.json
  • Transport: STDIO (maximum client compatibility)
  • Auth: supabase.auth.signInWithPassword() with user's email/password
  • Security: Uses anon key + RLS — each user can only access their own data
  • Database: Reads directly from Gym Tracker's Supabase tables (workouts, routines, exercise_catalog, training_plans)

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