A
Ai Powered Fitness App With MCP
by @firasyazid
MCP server by firasyazid
Created 10/30/2025
Updated about 14 hours ago
README
Repository documentation and setup instructions
AthleTech - AI-Powered Fitness Coaching App
AthleTech is a comprehensive fitness application that leverages AI to provide personalized workout plans and goal roadmaps based on user profiles and fitness objectives.
Project Structure
This is a monorepo containing two main components:
AthleTech/
├── AthleTech-front/    # React Native mobile app (Expo)
└── MCP-backend/        # FastAPI Python backend
Features
- User Authentication: Secure JWT-based authentication system
- Personalized Profiles: Detailed user profiles including fitness level, goals, and limitations
- AI Workout Generation: Custom workout plans generated based on user data
- Goal Roadmaps: AI-powered fitness goal planning and tracking
- Cross-Platform: Works on iOS, Android, and Web
Tech Stack
Frontend
- React Native with Expo
- TypeScript
- Expo Router (file-based routing)
- Axios for API communication
- AsyncStorage for local data persistence
Backend
- FastAPI (Python)
- MongoDB (Motor async driver)
- JWT authentication
- LLM integration for AI features
- Pydantic for data validation
Getting Started
Prerequisites
- Node.js (v18 or higher)
- Python 3.10+
- MongoDB (local or remote instance)
- Expo CLI
Backend Setup
- Navigate to the backend directory:
cd MCP-backend
- Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Create a .envfile (copy from.env.example):
cp .env.example .env
- Update the .envfile with your configuration:
MONGO_URL=mongodb://localhost:27017
SECRET_KEY=your-secret-key-here
HOST=0.0.0.0
PORT=8000
CORS_ORIGINS=http://localhost:8081
- Start the server:
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
Frontend Setup
- Navigate to the frontend directory:
cd AthleTech-front
- Install dependencies:
npm install
- Create a .envfile (copy from.env.example):
cp .env.example .env
- Update the .envfile with your backend URL:
EXPO_PUBLIC_API_URL=http://192.168.100.32:8000
Note: Replace with your machine's IP address or use http://localhost:8000 for local development.
- Start the Expo development server:
npx expo start
- Run on your preferred platform:
- Press ifor iOS simulator
- Press afor Android emulator
- Scan QR code with Expo Go app for physical device
 
- Press 
API Endpoints
Authentication
- POST /auth/register- Register a new user
- POST /auth/login- Login and receive JWT token
Workout
- GET /workout/generate- Generate personalized workout plan (requires authentication)
Goal Roadmap
- GET /goal-roadmap/generate- Generate fitness goal roadmap (requires authentication)
Environment Variables
Backend (MCP-backend/.env)
- MONGO_URL: MongoDB connection string
- SECRET_KEY: JWT secret key (use a strong random string)
- HOST: Server host (default: 0.0.0.0)
- PORT: Server port (default: 8000)
- CORS_ORIGINS: Comma-separated list of allowed origins
Frontend (AthleTech-front/.env)
- EXPO_PUBLIC_API_URL: Backend API base URL
Security Notes
- Never commit .envfiles to version control
- Use strong, randomly generated SECRET_KEYin production
- Configure CORS properly for production environments
- Use HTTPS in production
Development
Running Tests (Backend)
cd MCP-backend
pytest
Linting (Frontend)
cd AthleTech-front
npm run lint
Contributing
- Fork the repository
- Create a feature branch (git checkout -b feature/amazing-feature)
- Commit your changes (git commit -m 'Add amazing feature')
- Push to the branch (git push origin feature/amazing-feature)
- Open a Pull Request
License
This project is private and proprietary.
Contact
For questions or support, please open an issue in the repository.
Quick Setup
Installation guide for this server
Install Package (if required)
npx @modelcontextprotocol/server-ai-powered-fitness-app-with-mcp
Cursor configuration (mcp.json)
{
  "mcpServers": {
    "firasyazid-ai-powered-fitness-app-with-mcp": {
      "command": "npx",
      "args": [
        "firasyazid-ai-powered-fitness-app-with-mcp"
      ]
    }
  }
}