Deploy Remote MCP Servers in Python (Step by Step)
AI Summary
This video tutorial explains how to create remote MCP (Modular Control Protocol) servers using FastAPI and the FastMCP Python library. The MCP servers are hosted on a remote HTTP server, allowing multiple MCP servers to be available to clients or agents. It starts with an explanation of what MCP is — a protocol to connect AI agent clients with external toolkits or services. The example creates an MCP server with a web search tool integrated through the Tavili API to search the internet programmatically.
The video shows how to debug MCP servers using the Anthropics Inspector app, emphasizing the use of streamable HTTP transport and the correct URL endpoints to connect and test the server. It also demonstrates how to host multiple MCP servers within a single FastAPI application to avoid deploying multiple instances for each server.
Finally, the tutorial covers deploying the multi-MCP FastAPI application to Render, a cloud platform that allows easy deployment with a free tier. It includes steps for setting up the deployment environment, environment variables, and connecting to the deployed MCP servers remotely from clients like GitHub Copilot. The video ends with suggestions for future improvements, such as adding authentication to secure the remote MCP servers.