Will the gradual refinement of protocol standards such as MCP, A2A, and UnifAI mark the beginning of the second wave of AI Agent on-chain spring?
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Will the gradual refinement of protocol standards such as MCP, A2A, and UnifAI mark the beginning of the second wave of AI Agent on-chain spring?
AI agents will have a new wave of application-layer hype opportunities based on Web2 AI standard protocols (MCP, A2A, etc.).
Navigating Web3 tides with focused insightsWritten by: Haotian
Recently, on-chain AI Agents seem to be showing signs of recovery. Protocol standards such as MCP, A2A, and UnifAI are beginning to complement and interconnect with each other, forming a new infrastructure for Multi-AI Agent interactions—upgrading AI Agents from purely informational push services to execution-level application tools. The question is: could this mark the beginning of a second spring for on-chain AI Agents?
1) MCP (Model Context Protocol): An open standard protocol introduced by Anthropic, essentially acting as the "nervous system" connecting AI models with external tools, solving interoperability issues between Agents and external tools. Even Google DeepMind has expressed support, allowing MCP to quickly become an industry-recognized standard.
The technical value of MCP lies in standardizing function calls, enabling different LLMs to interact with external tools using a unified language—akin to the "HTTP protocol" of the Web3 AI world. However, it still has shortcomings in remote secure communication (@SlowMist_Team@evilcos have published multiple security analyses), especially when asset-related interactions become frequent.
2) A2A (Agent-to-Agent Protocol): A Google-led communication protocol framework between Agents, analogous to a "social network" for Agents. While MCP focuses on connecting AI tools, A2A emphasizes direct communication and interaction among Agents. Through mechanisms like Agent Cards, it solves capability discovery and enables cross-platform, multimodal Agent collaboration. It has already gained support from over 50 companies including Atlassian and Salesforce.
In terms of functionality, A2A resembles a "social protocol" for the AI world, allowing smaller AI systems to work together in a standardized way. Personally, beyond the protocol itself, Google’s involvement carries greater significance—as a major player endorsing and orchestrating the AI Agent ecosystem.
3) UnifAI: Positioned as an Agent collaboration network aiming to integrate the strengths of both MCP and A2A, providing SMEs with cross-platform Agent coordination solutions. Its design functions like a "middleware layer," seeking to enhance Agent ecosystem efficiency through unified service discovery. However, compared to other protocols, UnifAI currently lacks market influence and ecosystem maturity, and may eventually focus on specific niche scenarios.
@darkresearchai: A Solana-based implementation of an MCP server application that leverages TEE (Trusted Execution Environment) for security, enabling AI Agents to directly interact with the Solana blockchain—for example, querying account balances or issuing tokens.
The key innovation here is paving a path for AI Agents to empower DeFi by addressing trusted execution for on-chain operations. Its associated token $DARK has recently seen quiet逆势 growth, but given past experiences ("once bitten, twice shy"), I refrain from making recommendations. Still, DARK's application-layer expansion based on MCP does open up a novel direction.
So, what new directions and opportunities might emerge for on-chain AI Agents leveraging these standardized protocols?
1) Decentralized Execution Capabilities: Dark’s TEE-based architecture addresses a core challenge—how to enable AI models to execute on-chain actions in a trustworthy manner. This provides technical foundations for AI Agent adoption in DeFi, suggesting we may soon see more autonomous Agents handling transactions, token issuance, LP management, and other DeFi operations.
Compared to earlier concept-driven Agent models, ecosystems delivering real utility like this represent true value. (That said, Dark currently only offers 12 limited Actions on GitHub—promising start, but still far from moving fully beyond conceptual phase into mass adoption.)
2) Multi-Agent Collaborative Blockchain Networks: Explorations by A2A and UnifAI into multi-Agent collaboration introduce new possibilities for network effects within on-chain Agent ecosystems. Imagine a decentralized network composed of specialized Agents—this could surpass the limitations of individual LLMs, forming a self-coordinating decentralized market perfectly aligned with blockchain’s distributed nature.
That’s all.
Regardless, the AI Agent sector is gradually escaping the trap of being just another "meme." The development path for on-chain AI may first involve resolving cross-platform standardization (via MCP, A2A), followed by application-layer innovations (such as Dark’s experiments in DeFi).
A decentralized Agent ecosystem will likely form a new layered architecture: at the base, foundational security layers like TEE; in the middle, protocol standards such as MCP/A2A; and at the top, vertical-specific applications. (This could be bearish news for previous purely Web3-native AI protocol efforts? Shivering...)
For ordinary users, after experiencing the boom and bust of the first wave of on-chain AI Agents, the focus should no longer be on who can inflate the biggest market cap bubble, but rather on which projects genuinely solve core challenges in combining Web3 and AI—security, trustworthiness, and collaboration. To avoid falling into yet another bubble trap, my personal advice is to closely track whether project progress aligns with cutting-edge AI innovations in the Web2 space.
To summarize:
1. AI Agents will likely see a new wave of application-layer expansion and hype built upon Web2 AI standard protocols (e.g., MCP, A2A);
2. AI Agents are no longer content with standalone messaging services—execution-oriented tool services involving multi-Agent interaction and collaboration (DeFAI, GameFAI, etc.) will be the next frontier.
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Haotian | CryptoInsight
