Written by: Haotian
What would happen if Google's A2A and Anthropic's MCP protocol become the golden communication standard for web3 AI Agents? The intuitive feeling is "culture shock". In my view, the environment faced by web3 AI Agents differs significantly from the web2 ecosystem, and the challenges of implementing core communication protocols are entirely different:
1) Application Maturity Gap: A2A and MCP can quickly spread in the web2 domain because they serve already mature application scenarios, essentially acting as "value amplifiers" rather than value creators. Most web3 AI Agents are still in the primary stage of one-click Agent deployment, lacking deep application scenarios (such as DeFAI, GameFAI), making these protocols difficult to directly connect and create value.
For example, users can use MCP protocol as a connector when writing code in Cursor, publishing code updates to Github without leaving the current work environment. However, in a web3 environment, when a user tries to execute on-chain transactions with locally fine-tuned strategies, they might become completely lost when attempting to analyze on-chain data.
2) Fundamental Infrastructure Chasm: For web3 AI Agents to build a complete ecosystem, they must first fill the severely missing underlying infrastructure, including unified data layers, Oracle layers, intent execution layers, decentralized consensus layers, and so on. While A2A protocols in web2 environments allow Agents to easily call standardized APIs for functional collaboration, in web3 environments, even a simple cross-DEX arbitrage operation faces enormous challenges.
Imagine a scenario where a user instructs an AI Agent to "buy from Uniswap when ETH price falls below $1,600 and sell when the price recovers". This seemingly simple operation requires the Agent to simultaneously solve web3-specific problems like real-time on-chain data parsing, dynamic Gas fee optimization, slippage control, and MEV protection. In contrast, web2 AI Agents only need to call standardized APIs for functional collaboration, with infrastructure sophistication worlds apart from web3 environments.
3) Differentiated Web3 AI Construction Needs: Web3 AI Agents will struggle to leverage on-chain trading characteristics if they simply copy web2 protocols and functional models, especially given complex issues like data noise, transaction accuracy, and router diversity.
Take intent-based trading as an example. In a web2 environment, when a user instructs "book the cheapest flight", A2A protocol allows multiple Agents to collaborate easily. But in a web3 environment, when a user expects to "cross-chain USDC to Solana with the lowest cost and participate in liquidity mining", the Agent must not only understand user intent but also weigh security, atomicity, and cost erosion, executing a series of complex on-chain operations. In other words, if seemingly convenient operations expose users to greater security risks, such convenience is meaningless and represents a false need.
In conclusion, I want to express that while the value of A2A and MCP is undeniable, we cannot expect them to directly adapt to the web3 AI Agent track without modification. Isn't the infrastructure deployment blank an opportunity for Builders?
