The Model Context Protocol (MCP) is an open specification that simplifies connecting AI models to external tools and data sources. By implementing a custom MCP server, developers can expose data resources in a read-only way, define tools for the AI to call with actions or run functions, and optionally include prompts to standardize messages and tasks. A complete working weather server example demonstrates how to set up a Node.js project, implement a custom MCP server using the modelcontextprotocol TypeScript SDK, review the code, connect it to Claude Desktop, and try it out. The MCP lifecycle is explained, including how Claude reads the configuration file, spawns the server process, connects stdio pipes, announces its capabilities, receives requests, processes them, and displays the results to the user. Next steps include adding more tools, resources, using SSE transport, experimenting with prompts, and integrating the custom server with other MCP clients.