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.
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 yourgym-tracker-mcpdirectory.
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)
Tech stack
- Model Context Protocol SDK
- Supabase JS Client
- Zod (schema validation)
- TypeScript + Node.js
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