文章摘要
The Model Context Protocol (MCP) is a framework designed to extend the effective context window of large language models (LLMs) by allowing AI assistants to request and receive relevant information from external servers. MCP operates on a client-server model, where AI assistants (clients) make requests to MCP servers for specific contextual data. This protocol enables AI models, such as Claude, to access up-to-date information, execute tools, and integrate with external APIs beyond their initial training data. Servers provide context by embedding information as `tool_code`, `tool_description`, or `tool_response` tags within the conversation history, which the client model then processes. MCP facilitates the creation of more capable and dynamic AI assistants that can perform complex, real-world tasks by leveraging external knowledge and functionality.