Frequently Asked Questions (FAQ) about the TransportAI MCP Server

Q: What is the TransportAI MCP Server? A: The TransportAI MCP Server is a backend server that implements the Model Context Protocol (MCP) and integrates with the AviationStack API to provide AI models with real-time flight data.

Q: What is MCP (Model Context Protocol)? A: MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), allowing AI models to access and interact with external data sources.

Q: What is the AviationStack API? A: The AviationStack API is a real-time flight data API that provides information about flight status, schedules, and other relevant data.

Q: How do I set up the TransportAI MCP Server locally? A: 1. Create a virtual environment. 2. Install dependencies using pip install -r requirements.txt. 3. Create a .env file with your AviationStack API key. 4. Start the server using uvicorn main:app --reload in the server directory.

Q: How do I deploy the TransportAI MCP Server to Smithery AI? A: 1. Build the Docker image using docker build -t transportai-mcp .. 2. Create a new project in Smithery AI. 3. Upload the Dockerfile and related files. 4. Set the environment variable AVIATIONSTACK_API_KEY. 5. Deploy the application.

Q: How do I test the MCP Server? A: Use curl to send a POST request to the /mcp/query endpoint with a JSON payload containing a query for flight information. Example:

bash 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”} }’

Q: What is the license of the TransportAI MCP Server? A: The TransportAI MCP Server is released under the MIT License.

Q: How does UBOS enhance the TransportAI MCP Server? A: UBOS is a full-stack AI Agent Development Platform that simplifies the process of orchestrating AI Agents, connecting them with enterprise data, building custom AI Agents with LLM models, and creating Multi-Agent Systems. It allows seamless integration with MCP Servers, streamlining the AI agent development process.