文章摘要
The article details the process of building and deploying a Model Context Protocol (MCP) server, designed to provide external tool access and context for AI assistants.
- It demonstrates setting up a simple MCP server using Heroku and Python, focusing on managing context and tool definitions.
- The guide shows how to integrate this custom MCP server with the Cursor AI code editor, allowing Cursor to leverage the server's defined tools and context.
- The example MCP server includes a tool for fetching information from a GitHub repository, illustrating how AI can interact with external systems.
- The server's setup involves using FastAPI for the web service and defining a custom `ToolLoader` for dynamic tool discovery.