TransportAI MCP Server

This is the backend server for the TransportAI project, implementing the Model Context Protocol (MCP) and integrating with the AviationStack API.

Project Structure

TransportAI/
├── server/             # FastAPI backend
│   └── main.py        # Main server file
├── Dockerfile         # Docker configuration
├── requirements.txt   # Python dependencies
└── .env              # Environment variables

Setup Instructions

Local Development

1. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venvScriptsactivate

2. Install dependencies:

pip install -r requirements.txt

3. Create a .env file in the root directory and add your AviationStack API key:

AVIATIONSTACK_API_KEY=your_api_key_here

4. Start the server:

cd server
uvicorn main:app --reload

Smithery AI Deployment

1. Ensure you have Docker installed on your system

2. Build the Docker image:

docker build -t transportai-mcp .

3. Test the Docker image locally:

docker run -p 8000:8000 -e AVIATIONSTACK_API_KEY=your_api_key_here transportai-mcp

4. Deploy to Smithery AI:
   • Create a new project in Smithery AI
   • Upload the Dockerfile and related files
   • Set the environment variable AVIATIONSTACK_API_KEY
   • Deploy the application

API Endpoints

MCP Protocol Endpoints

• GET /: Server status and version information
• GET /mcp/health: Health check endpoint
• POST /mcp/query: Main MCP query endpoint
  • Request body:

    {
      "context": {
        "session_id": "optional_session_id"
      },
      "query": "Get information for flight TK123",
      "parameters": {
        "flight_iata": "TK123"
      }
    }
    

Testing the MCP Server

You can test the MCP server using curl:

curl -X POST http://localhost:8000/mcp/query 
  -H "Content-Type: application/json" 
  -d '{
    "context": {"session_id": "test_session"},
    "query": "Get information for flight TK123",
    "parameters": {"flight_iata": "TK123"}
  }'

License

MIT