MCP: The Key Infrastructure of the Web3 AI Agent Ecosystem

MCP (Model Context Protocol) 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. As an emerging concept in the Web3 AI field, MCP originates from Web2 AI and is now being reimagined in the Web3 environment.

MCP Overview

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

The importance of ### MCP

Current large language models face several core limitations:

• 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, bridging these capability gaps and enabling AI Agents to utilize a variety of tools. MCP can be likened 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 benefits both AI Agents (clients) and tool developers (servers), ultimately creating a more open, interoperable, and low-friction AI ecosystem.

The difference between MCP and traditional APIs

Traditional API design is primarily focused on human use rather than 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 documents and must be hard-coded to adapt to each API.

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

Web3 AI and MCP Ecosystem

AI in Web3 also faces the issues of "lack of contextual data" and "data islands." A new generation of AI Agent infrastructure and applications based on the MCP and A2A protocols is emerging, specifically designed for Web3 scenarios, allowing Agents to access multi-chain data and natively interact with DeFi protocols.

Project Case

DeMCP

DeMCP is a decentralized marketplace for MCP Servers, focusing on native encryption 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 a token incentive mechanism to encourage developers to contribute to the MCP server.
• Provide MCP aggregator and micropayment features to lower the usage threshold.

DeepCore

DeepCore provides an MCP Server registration system, focusing on the cryptocurrency field, and further expanding into 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 brief:

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

Blockchain and MCP Server

The MCP Server integrates blockchain technology with multiple benefits:

1. Obtain long-tail data through the native incentive mechanism of encryption.
2. Defend against "tool poisoning" attacks
3. Introduce a staking/penalty mechanism to build the trust system of the MCP server.
4. Improve system fault tolerance and real-time performance
5. Promote Open Source Innovation

Future Trends and Industry Impact

More and more people in the crypto industry are beginning to realize the potential of MCP in connecting AI and blockchain. 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 could become an MCP client, and every API could be an MCP server. This may give rise to new pricing mechanisms: Agents can dynamically select tools based on execution speed, cost efficiency, relevance, etc., forming a more efficient Agent service economy empowered by cryptography and blockchain.

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