为何下一轮 AI Agent 热潮一定基于 MCP+A2A 等 Web2AI 标准框架协议?

深潮TechFlowPublished on 2025-04-18Last updated on 2025-04-19

Abstract

总之一句话,下一波 AI Agent 的新势头正在酝酿,但不再是过去纯叙事炒概念的姿态,而必须靠实用主义和应用落地才能支撑。

下一波 AI Agent 的新势头正在酝酿,但不再是过去纯叙事炒概念的姿态,而必须靠实用主义和应用落地才能支撑。


撰文:Haotian


为何我会断言,下一轮 AI Agent 热潮一定会基于 MCP+A2A 等 web2AI 标准框架协议?背后的逻辑很简单:


1)web3 AI Agent 的困境在于过度概念化,叙事大于实用,当在讨论去中心化平台未来,用户数据主权的宏大愿景时,实际产品应用的用户体验却惨不忍睹。尤其是已经经历了一轮概念化泡沫洗礼的情况下,已经很少有散户愿意为宏大且无法兑现的预期买单了;


2)web2 AI 领域的 MCP、A2A 等协议标准能快速崛起并在 AI 圈形成较大势能就源于其「看得见、摸得着」的实用主义。MCP 就像是 AI 世界的 USB-C 接口,让 AI 模型能够无缝连接到各种数据源和工具,且已经有很多 MCP 实用案例,


比如:有用户直接可以用 Claude 控制 Blender 制作 3D 模型,还有一些 UI/UX 从业者可以用自然语言生成完整的 Figma 设计文件,一些程序员也可以直接用 Cursor 一站式完成代码编撰补充和 Git 提交等等操作。


3)之前大家预期 web3 AI Agent 能够在 DeFai、GameFai 两大垂直场景有创新落地的应用诞生,但实际上好多类似的应用还停留在自然语言处理界面「秀技」层级,根本够不上实用性的门槛。


而通过 MCP 和 A2A 的结合,可以构建更强大的 Multi-Agent 协作系统,将复杂任务分解给专门的 Agent 来处理。比如,让分析 Agent 来读取链上数据、分析市场走势,并串联其他预测 Agent、风控 Agent,把过去单一 Agent 一体化执行的思路转变为多 Agent 协作分工执行的范式。


以上,所有 MCP 成功的应用案例,都为 web3 新一代交易、游戏 Agent 的诞生提供了成功范例。


除了这些之外,基于 MCP 和 A2A 的混合框架标准,还有面向 web2 用户的友好性和应用落地速度等优势,眼下只需要考虑如何把 web3 的价值捕获和激励机制以及 DeFai、GameFai 等应用场景结合起来即可。如果还在一位坚守 web3 纯概念主义而拒绝拥抱 web2 实用主义的项目,恐怕会错过下一轮的 AI Agent 新趋势。


总之一句话,下一波 AI Agent 的新势头正在酝酿,但不再是过去纯叙事炒概念的姿态,而必须靠实用主义和应用落地才能支撑。

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