AI Agent's second spring? MCP, A2A, UnifAI may be a new paradigm for hype

Recently, on-chain AI Agent seems to have signs of recovery. MCP, A2A, UnifAI and other protocol standards are complementary and connected to become the new Multi-AI Agent interactive infrastructure, upgrading AI Agent from pure information push services to execution application tool service level. The question is, will this be the beginning of the second wave of AI Agent on the chain?

1. MCP (Model Context Protocol): Anthropic's open standard protocol is essentially to open up the "nervous system" between AI models and external tools, and solve the interoperability problem between Agent and external tools. Google DeepMind has expressed support for it, making MCP quickly accredited protocol standard for the industry.

The technical value of MCP lies in standardizing function calls so that different LLMs can interact with external tools in a unified language, which is equivalent to the "HTTP protocol" in the Web3 AI world, but it still has shortcomings in the remote security communication process (@SlowMist_Team @evilcos has analyzed many security reports), especially after the interaction behaviors involving assets are intensive;

2. A2A (Agent-to-Agent Protocol): Google-led inter-agent communication protocol, similar to the protocol framework of "Agent social network". Compared with MCP focusing on AI tool connections, A2A focuses more on communication interactions between agents. Through the Agent Card mechanism, we can solve capabilities and discover problems and realize cross-platform and multi-modal Agent collaboration. We have received support from more than 50 companies including Atlassian and Salesforce.

From a functional perspective, A2A is more like a "social protocol" in the AI ​​world, allowing different small AIs to work together in a unified way. I personally feel that except for the agreement, Google's "acquisition" endorsement of AI Agent is more meaningful.

3. UnifAI: Positioned as an Agent collaboration network, it attempts to integrate the advantages of MCP and A2A to provide cross-platform Agent collaboration solutions for small and medium-sized enterprises. Its layout is similar to a "middle layer", hoping to make the Agent ecosystem more efficient through a unified service discovery mechanism. However, compared with several other protocols, UnifAI's market influence and ecological construction are still insufficient, and it may focus on a certain segmented scenario in the future.

@darkresearchai: It is an MCP server application implementation based on Solana blockchain. It provides security guarantees through TEE trusted execution environment, allowing AI Agent to directly interact with the Solana blockchain, such as: querying account balances, issuing tokens, etc.

The biggest highlight of this protocol is that it empowers the AI ​​Agent to select paths for DeFi, solving the trusted execution problem of on-chain operations. Its corresponding Ticker $DARK has been quietly rising against the trend recently, but based on the cautious attitude of being bitten by a snake and being afraid of the rope for ten years, I will not recommend it here. However, DARK's implementation and expansion of the application layer based on MCP has indeed opened up a new direction.

The question is, what expansion directions and opportunities can be generated by the on-chain AI Agent with the help of these standardized protocols?

1. Decentralized execution application capabilities: Dark's TEE-based design solves a core problem - how to make AI models perform on-chain operations trustworthy. This provides technical support for the implementation of AI Agent in the DeFi field, which means that in the future, more AI Agents that independently execute DeFi operations such as transactions, token issuance, and LP management may appear.

Compared with the Agent models that were purely concept hyped in the past, this practical value of the Agent ecosystem is the real value. (However, Dark currently only has a limited 12 Actions, which can only be considered a good start. It is still a long way from the complete departure from the concept stage to the implementation of large-scale applications)

2. Multi-Agent collaborative blockchain network: A2A and UnifAI's exploration of multi-Agent collaboration scenarios has brought new network effect possibilities to the on-chain Agent ecosystem. Imagine a decentralized network composed of multiple professional agents that may break through the capability boundaries of a single LLM and form an autonomous and collaborative decentralized market, which is perfectly in line with the characteristics of blockchain distributed networks.

above.

In any case, the AI ​​Agent track is getting rid of the dilemma of "MEMEization". The development path of on-chain AI may be to first solve cross-platform standard problems (MCP, A2A) and then to derive application layer innovation (such as Dark's attempts in the DeFi field).

The decentralized Agent ecosystem will form a new layered expansion architecture: the underlying layer is basic security guarantees such as TEE, the middle layer is protocol standards such as MCP/A2A, and the upper layer is specific vertical scenario applications. (This may be a negative for the once pure web3 AI standard protocol? It's trembling.)

For ordinary users, after experiencing the first wave of AI Agent chain, what they need to pay attention to is no longer who can hype up the largest market value bubble, but who can truly solve the core pain points such as security, credibility, and collaboration in the process of combining Web3 and AI. As for how to avoid falling into another bubble trap, I personally think it would be better to observe whether the project progress can be closely related to web2's AI technology innovation.

To summarize:

1. AI Agent will have a new wave of application layer extension and hype opportunities based on the web2 AI standard protocol (MCP, A2A, etc.);

2. AI Agent is no longer satisfied with single message push services. Execution tool services (DeFAI, GameFAI, etc.) that interact and collaborate with multiple AI Agents will be a new highlight.