Why the next wave of AI Agent craze will be based on the Web2 AI standard framework

Author: Haotian

Why do I assert that the next round of AI Agent craze will definitely be based on web2AI standard framework protocols such as MCP+A2A? The logic behind it is simple:

1) The dilemma of web3 AI Agent lies in over-conceptualization, with narrative outweighing practicality. When discussing the grand vision of the future of decentralized platforms and user data sovereignty, the user experience of actual product applications is terrible. Especially after experiencing a round of conceptual bubble baptism, few retail investors are willing to pay for grand and unfulfilled expectations;

2) The rapid rise of MCP, A2A and other protocol standards in the web2 AI field and the formation of greater potential in the AI ​​circle stems from their "visible and tangible" pragmatism. MCP is like the USB-C interface in the AI ​​world, allowing AI models to seamlessly connect to various data sources and tools, and there are already many practical cases of MCP. For example, some users can directly use Claude to control Blender to make 3D models, and some UI/UX practitioners can use natural language to generate complete Figma design files. Some programmers can also use Cursor to complete code compilation and Git submission in one stop. 3) Previously, everyone expected that web3 AI Agent would be able to have innovative applications in the two major vertical scenarios of DeFai and GameFai, but in fact, many similar applications are still at the "show skills" level of natural language processing interfaces, and they are not practical at all. Through the combination of MCP and A2A, a more powerful Multi-Agent collaboration system can be built to decompose complex tasks to specialized Agents for processing. For example, let the analysis agent read the on-chain data, analyze the market trend, and connect other prediction agents and risk control agents in series, so as to transform the idea of ​​single agent integrated execution in the past into a paradigm of multi-agent collaborative division of labor execution.

All the above successful application cases of MCP have provided successful examples for the birth of the new generation of web3 transactions and game agents.

In addition to these, the hybrid framework standard based on MCP and A2A also has advantages such as friendliness for web2 users and application landing speed. At present, we only need to consider how to combine the value capture and incentive mechanism of web3 with application scenarios such as DeFai and GameFai. If you are still a project that adheres to the pure conceptualism of web3 and refuses to embrace the pragmatism of web2, you may miss the next round of new trends of AI Agent.

In a word, the new momentum of the next wave of AI Agent is brewing, but it is no longer the pure narrative concept of the past, but must be supported by pragmatism and application landing.