文章摘要
The article outlines how to build AI agents using the Model Context Protocol (MCP), emphasizing its role in allowing AI agents to interface with external tools and real-world systems.
- MCP serves as a standard for AI assistants, like Claude, to discover and utilize external tools and services, expanding their capabilities beyond their core language model.
- It defines a communication mechanism where an MCP Server hosts tools, and an MCP Client (the AI agent) requests and executes these tools through a defined JSON-based protocol.
- The protocol facilitates actions such as tool discovery, invocation with arguments, and receiving structured results back to the AI agent.
- A practical guide is provided for setting up an MCP server and integrating it with an AI client using Python, demonstrating how to create custom tools for an agent.