MCP Server

A Model-Controller-Provider (MCP) architecture based server implementation using FastAPI.

Project Structure

.
├── api/              # API routes and endpoints
│   └── v1/          # API version 1
│       ├── __init__.py
│       └── items.py # Item endpoints
├── controllers/      # Business logic and request handlers
│   └── item_controller.py
├── providers/       # Data access and external service integrations
│   └── item_provider.py
├── models/         # Data models and database schemas
│   └── item.py
├── core/          # Core configurations and utilities
│   ├── config.py  # Application configuration
│   └── database.py # Database configuration
├── main.py        # Application entry point
├── requirements.txt # Project dependencies
├── environment.yml  # Conda environment file
└── README.md      # Project documentation

Features

• FastAPI-based REST API: High-performance, easy to use, fast to code
• MCP Architecture:
  • Models: Data structures and database schemas
  • Controllers: Business logic and request handling
  • Providers: Data access and external service integration
• Modern Tech Stack:
  • SQLAlchemy for ORM
  • Pydantic for data validation
  • FastAPI for API framework
  • SQLite for development database
• API Features:
  • Automatic OpenAPI documentation
  • Request validation
  • Response serialization
  • CORS middleware
  • Type checking

Setup

1. Create a Conda environment:

# Create a new environment with Python 3.12
conda create -n codeMcpServer python=3.12
# Activate the environment
conda activate codeMcpServer

2. Install dependencies:

# Using the provided environment file (recommended)
conda env create -f environment.yml

# OR using pip 
pip install -r requirements.txt

# OR using conda with conda-forge channel
conda config --add channels conda-forge
conda install --file requirements.txt

3. Run the server:

uvicorn main:app --reload

The server will start at http://localhost:8000

Dependencies

Key dependencies in this project:

• Python 3.12.9
• FastAPI 0.112.2
• SQLAlchemy 2.0.37
• Pydantic 2.11.2
• Uvicorn 0.32.1
• Python-dotenv 0.21.0

For a complete list, see environment.yml or requirements.txt.

Environment Management

Export Environment

To export your environment for sharing:

# Export full environment with exact versions (without prefix)
conda env export | grep -v "^prefix: " > environment.yml

# Or export only manually installed packages
conda env export --from-history > environment.yml

Import Environment

To recreate an environment from the exported file:

conda env create -f environment.yml

API Documentation

Once the server is running, you can access:

• Interactive API documentation (Swagger UI): http://localhost:8000/docs
• Alternative API documentation (ReDoc): http://localhost:8000/redoc

API Endpoints

Items API (/api/v1/items)

• GET /api/v1/items/: List all items
• GET /api/v1/items/{item_id}: Get a specific item
• POST /api/v1/items/: Create a new item
• PUT /api/v1/items/{item_id}: Update an item
• DELETE /api/v1/items/{item_id}: Delete an item

Development

Project Organization

The project follows the MCP (Model-Controller-Provider) pattern:

• Models: Define data structures and database schemas
• Controllers: Handle business logic and request processing
• Providers: Manage data access and external service integration

Adding New Features

1. Create the model in models/
2. Create the provider in providers/
3. Create the controller in controllers/
4. Create the API endpoints in api/v1/

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the terms of the LICENSE file included in the repository.