📄 中文摘要
随着人工智能的快速发展，许多开发者在早期阶段仅仅通过将 API 密钥嵌入聊天完成中来实现所谓的“AI 集成”，尽管用户对此感到满意，但开发者始终觉得存在某种缺失。AI 在孤立环境中表现出色，但一旦需要与开发者的系统交互，就显得无能为力。MCP（模型上下文协议）的出现为解决这一问题提供了新的思路。MCP 使得 AI 能够更好地理解和利用开发者的数据库、内部 API、文件系统以及应用程序所依赖的实时上下文，从而提升了 AI 的实用性和智能化水平。
构建 MCP 服务器的经验教训：开发者的实用指南
出处: What I Learned Building with MCP Servers
发布: 2026年3月5日
📄 English Summary
What I Learned Building with MCP Servers
Many developers initially approached AI integration by simply plugging API keys into chat completions, which satisfied users but left a sense of inadequacy. The AI performed well in isolation but struggled when interacting with the developer's system, lacking awareness of databases, internal APIs, file systems, and live context. The introduction of Model Context Protocol (MCP) offers a solution to these limitations. MCP enables AI to better understand and utilize the developer's databases, internal APIs, file systems, and the real-time context that applications depend on, enhancing the practicality and intelligence of AI systems.