Core Viewpoint - The MCP (Model Context Protocol) has gained significant attention in the AI field due to the rise of Manus and Agent, with major companies like OpenAI, Microsoft, and Google supporting it, alongside domestic players like Alibaba Cloud and Tencent Cloud launching rapid deployment platforms [1][2]. Group 1: MCP Overview - MCP is designed to facilitate the integration of external services and functionalities into AI applications, acting as a universal interface for communication between AI applications (clients) and various external extensions (MCP servers) [5][6]. - The protocol emphasizes interaction patterns and aims to make AI applications more extensible, akin to a USB-C interface for connecting to an ecosystem [7][8]. - The concept of MCP was inspired by an internal project called LSP (Language Server Protocol), aiming to standardize communication between AI applications and extensions [8][10]. Group 2: Development and Design Principles - The MCP team focused on simplifying the server construction process, allowing for rapid development and iteration using AI-assisted coding [8][12]. - The design principles of MCP include ensuring that tools are controlled by the model rather than the user, allowing for a more seamless integration of functionalities [31][32]. - MCP is not in opposition to open APIs; rather, they are complementary, with each serving different purposes depending on the task at hand [33][34]. Group 3: Future Directions and Innovations - The future of AI applications and agents is expected to lean towards statefulness, which is a topic of ongoing debate within the MCP core team [56]. - There is potential for innovative applications that go beyond simple API wrappers, such as memory MCP servers that allow LLMs to retain information across interactions [34][35]. - The MCP protocol is designed to be flexible, allowing for the integration of various functionalities and the potential for recursive interactions between different MCP servers [50][51]. Group 4: Security and Authorization - The next version of the MCP protocol will include authentication specifications, focusing on user-to-server authorization using OAuth 2.1 or its modern subsets [57][58]. - The design aims to be minimalistic, addressing real pain points without overcomplicating the protocol, ensuring backward compatibility [58][59]. - The protocol's programming language agnosticism allows for a standardized interface, reducing the need for separate SDKs for different programming languages [62].

Anthropic 在去年发布的 MCP 协议，今年因为 Manus 和 Agent 的热潮，突然成为了 AI 领域最热门的协议。OpenAI、微软、Google 等大厂也纷 纷支持协议，国内阿里云百炼、腾讯云也迅速跟进，上线了快速搭建平台。 但争议也不少，很多人质疑 MCP 和 API 区别不大、Anthropic 的工程师对互联网协议不怎么精通、以及协议太简单带来的安全问题等等。 让 MCP 协议的发明者来回答这些问题，再合适不过了。 在 Latent Space 最近的一起播客中，他们邀请到了 Anthropic 团队 MCP 协议的发明者——Justin Spahr-Summers、 David Soria Parra，详细聊 了聊 MCP 的起源，以及他们对于 MCP 诸多想法：为何推出 MCP、 MCP 与现有的 API 有何不同、如何让 MCP 更好利用好工具等等。信息量很 大，建议收藏阅读。 对谈嘉宾介绍： TLDR: Founder Park 正在搭建开发者社群，邀请积极尝试、测试新模型、新技术的开发者、创业者们加入，请扫码详细填写你的产品/项目信息，通过审核 后工作人员会拉你入群～ 进群之 ...