Model Context Protocol (MCP) Server

A FastAPI-based server implementing the Model Context Protocol for providing contextual information to AI models. This server acts as a middleware between AI models and various data sources, intelligently routing queries to the most appropriate data provider.

Features

• Intelligent query routing based on query analysis
• Support for multiple data sources (Database, GraphQL, REST)
• Integration with Ollama models (Mistral, Qwen, Llama2)
• Environment-aware configuration (Development/Production)
• Comprehensive logging and error handling
• Health check endpoints
• Mock data support for development

Prerequisites

• Python 3.8+
• Ollama installed and running locally
• Required Ollama models:
  • mistral
  • qwen
  • llama2

Installation

1. Clone the repository:

git clone <repository-url>
cd mcp-server

2. Create and activate a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Create a .env file:

cp .env.example .env

5. Update the .env file with your configuration:

ENVIRONMENT=development
OLLAMA_MODEL=mistral
OLLAMA_BASE_URL=http://localhost:11434

Running the Server

1. Start Ollama (if not already running):

ollama serve

2. Start the MCP server:

python main.py

The server will be available at http://localhost:8000

API Endpoints

Get Context

curl -X POST http://localhost:8000/context \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Tell me about iPhone 15",
    "model": "mistral"
  }'

List Available Models

curl http://localhost:8000/models

Health Check

curl http://localhost:8000/health

Project Structure

mcp-server/
├── context_providers/     # Data source providers
│   ├── database.py       # Database provider
│   ├── graphql.py        # GraphQL provider
│   ├── rest.py          # REST API provider
│   └── provider_factory.py
├── model_providers/      # AI model providers
│   ├── base.py          # Base model provider
│   ├── ollama.py        # Ollama integration
│   └── provider_factory.py
├── main.py              # FastAPI application
├── query_analyzer.py    # Query analysis logic
├── logger_config.py     # Logging configuration
├── requirements.txt     # Project dependencies
└── README.md           # Project documentation

Development

Adding New Providers

1. Create a new provider class in the appropriate directory
2. Implement the required interface methods
3. Register the provider in the factory

Adding New Models

1. Add the model to the AVAILABLE_MODELS dictionary in model_providers/ollama.py
2. Update the model validation logic if needed

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 MIT License - see the LICENSE file for details.