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在大型语言模型（LLM）与企业级软件系统的集成进程中，上下文提供的摩擦力一直是限制人工智能应用深度的核心瓶颈。传统的架构范式高度依赖于静态的检索增强生成（RAG）管道或高度定制化、紧密耦合的应用程序接口（API）集成。这些传统方法不仅维护成本高昂，且难以适应底层数据模式的动态演进。模型上下文协议（Model Context Protocol, MCP）的出现从根本上改变了这一现状，它为人工智能系统 ...