MCP: The Infrastructure Revolution of Web3 AI Agent Ecosystem

MCP: The Core Infrastructure of the Web3 AI Agent Ecosystem

MCP is rapidly becoming a core component of the Web3 AI Agent ecosystem. It introduces the MCP Server through a plugin-like architecture, providing new tools and capabilities for AI Agents. Similar to other emerging concepts in the Web3 AI field, MCP (Model Context Protocol) originates from Web2 AI and is now being reimagined in the Web3 context.

MCP Overview

MCP is an open protocol designed to standardize the way applications convey contextual information to large language models (LLMs). This enables tools, data, and AI Agents to collaborate more seamlessly.

The importance of MCP ###

The main limitations faced by current large language models include:

  • Unable to browse the internet in real time
  • Unable to directly access local or private files
  • Unable to interact autonomously with external software

MCP acts as a universal interface layer, filling these capability gaps and enabling AI Agents to utilize various tools.

MCP can be compared to a unified interface standard in the field of AI applications, making it easier for AI to connect with various data sources and functional modules. This standardized protocol is beneficial for both AI agents and tool developers:

  • AI Agent can safely connect to external tools and real-time data sources.
  • Tool developers can achieve one-time integration for cross-platform use.

The final result is a more open, interoperable, and low-friction AI ecosystem.

Interpretation of MCP: The Core Engine Driving the Next Generation of Web3 AI Agents

The difference between MCP and traditional APIs

The design of traditional APIs is meant for human use, not AI-first. Each API has its own structure and documentation, and developers must manually specify parameters and read the interface documentation. The AI Agent itself cannot read the documentation and must be hard-coded to adapt to each API.

MCP abstracts these unstructured parts by standardizing the function call format within the API, providing a unified calling method for Agents. MCP can be seen as an API adaptation layer encapsulated for autonomous Agents.

Interpretation of MCP: The Core Engine Driving the Next Generation of Web3 AI Agents

Web3 AI and MCP Ecosystem

AI in Web3 also faces the issues of "lack of contextual data" and "data silos," meaning that AI cannot access on-chain real-time data or natively execute smart contract logic.

In the past, some projects attempted to build multi-agent collaborative networks, but ultimately fell into the "reinventing the wheel" dilemma due to reliance on centralized APIs and custom integrations. Each time a data source was integrated, the adaptation layer had to be rewritten, leading to skyrocketing development costs.

To address this bottleneck, the next generation of AI Agents requires a more modular, Lego-like architecture to facilitate the seamless integration of third-party plugins and tools. The new infrastructure and applications for AI Agents based on MCP and A2A protocols are emerging, specifically designed for Web3 scenarios, allowing Agents to access multi-chain data and natively interact with DeFi protocols.

Interpreting MCP: The Core Engine Driving the Next Generation Web3 AI Agent

Project Case

DeMCP

DeMCP is a decentralized marketplace for MCP Servers, focusing on native cryptographic tools and ensuring the sovereignty of MCP tools. Its advantages include:

  • Use TEE (Trusted Execution Environment) to ensure that the MCP tool has not been tampered with.
  • Use token incentive mechanisms to encourage developers to contribute to MCP servers
  • Provide MCP aggregator and micropayment functions to lower the usage threshold.

Interpretation of MCP: The Core Engine Driving the Next Generation Web3 AI Agent

DeepCore

DeepCore provides an MCP Server registration system, focusing on the cryptocurrency field, and further expanding into another open standard proposed by Google: the A2A (Agent-to-Agent) protocol.

A2A is an open protocol designed to enable secure communication, collaboration, and task coordination between different AI agents. It supports enterprise-level AI collaboration, allowing AI agents from different companies to work together on tasks.

In short:

  • MCP: Provides tools for Agent access capabilities
  • A2A: Provides agents with the ability to collaborate with each other.

Interpretation of MCP: The Core Engine Driving the Next Generation Web3 AI Agent

The Combination of MCP Servers and Blockchain

The MCP Server integrates blockchain technology with various benefits:

  1. Acquire long-tail data through the native encryption incentive mechanism, encouraging the community to contribute scarce datasets.
  2. Defend against "tool poisoning" attacks, where malicious tools disguise themselves as legitimate plugins to mislead the Agent.
  3. Introduce a staking/punishment mechanism to build the trust system of the MCP server in conjunction with the on-chain reputation system.
  4. Enhance the system's fault tolerance and real-time capabilities to avoid single points of failure in centralized systems.
  5. Promote open-source innovation, allowing small developers to release ESG data sources and enrich ecological diversity.

Currently, most MCP Server infrastructure still matches tools by parsing user natural language prompts. In the future, AI Agents will be able to independently search for the required MCP tools to accomplish complex task objectives.

Interpretation of MCP: The Core Engine Driving the Next Generation of Web3 AI Agents

Future Trends and Industry Impact

As infrastructure matures, the competitive advantage of "developer-first" companies will shift from API design to providing a richer, more diverse, and easily combinable toolkit.

In the future, every application may become an MCP client, and every API may become an MCP server. This could give rise to new pricing mechanisms: Agents can dynamically choose tools based on execution speed, cost efficiency, relevance, etc., forming a more efficient Agent service economy empowered by cryptocurrency and blockchain.

Interpretation of MCP: The Core Engine Driving the Next Generation Web3 AI Agent

MCP itself is a foundational protocol layer, and its true value and potential can only be truly seen when AI Agents integrate it and transform it into practical applications.

Ultimately, the Agent is the carrier and amplifier of MCP capabilities, while blockchain and cryptographic mechanisms build a trustworthy, efficient, and composable economic system for this intelligent network.

Interpretation of MCP: The Core Engine Driving the Next Generation Web3 AI Agent

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DegenMcsleeplessvip
· 07-28 07:37
It's just blowing concepts again, what's the big use?
View OriginalReply0
GasFeeWhisperervip
· 07-28 07:31
Um, I've played with this thing, and I feel the prospects are okay.
View OriginalReply0
FlashLoanLordvip
· 07-28 07:23
This thing can't be on the chain, right?
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AirdropGrandpavip
· 07-28 07:12
A new protocol again, right? It's copied, isn't it?
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