深入探讨MCP与AI工具的未来

Since OpenAI released function calling in 2023, I’ve been thinking about what it would take to unlock an ecosystem of agent and tool use. As the foundational models get more intelligent, agents’ ability to interact with external tools, data, and APIs becomes increasingly fragmented: Developers need to implement agents with special business logic for every single system the agent operates in and integrates with. 

自从 OpenAI 在 2023 年发布函数调用以来，我一直在思考解锁代理和工具使用生态系统需要什么。随着基础模型变得越来越智能，代理与外部工具、数据和 API 的交互能力变得越来越分散：开发者需要为代理操作和集成的每一个系统实现具有特殊业务逻辑的代理。

It’s clear that there needs to be a standard interface for execution, data fetching, and tool calling. APIs were the internet’s first great unifier—creating a shared language for software to communicate — but AI models lack an equivalent.

显然，需要有一个标准接口用于执行、数据获取和工具调用。API曾是互联网的第一个伟大统一者——为软件之间的通信创建了共享语言——但AI模型缺乏相应的东西。

Model Context Protocol (MCP), introduced in November 2024, has gained significant traction within developer and AI communities as a potential solution. In this post, we’ll explore what MCP is, how it changes the way AI interacts with tools, what developers are already building with it, and the challenges that still need solving. 

模型上下文协议（MCP）于2024年11月推出，在开发者和AI社区中获得了显著关注，成为一种潜在解决方案。在这篇文章中，我们将探讨MCP是什么，它如何改变AI与工具的交互方式，开发者已经在用它构建什么，以及仍需解决的挑战。

Let’s dive in.

让我们深入了解。

MCP is an open protocol that allows systems to provide context to AI models in a manner that’s generalizable across integrations. The protocol defines how the AI model can call external tools, fetch data, and interact with services. As a concrete example, below is how the Resend MCP server works with multiple MCP clients. 

MCP是一个开放协议，允许系统以可跨集成通用的方式为AI模型提供上下文。该协议定义了AI模型如何调用外部工具、获取数据和与服务交互。作为一个具体的例子，下面是Resend MCP服务器如何与多个MCP客户端协同工作的示例。

The idea is not new; MCP took inspiration from the LSP (Language Server Protocol). In LSP, when a user types in an editor, the client queries the language server to autocomplete suggestions or diagnostics.

这个想法并不新颖；MCP 从 LSP（语言服务器协议）中获得灵感。在 LSP 中，当用户在编辑器中输入时，客户端查询语言服务器以自动完成建议或诊断。

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