MCP: The Core Driving Force of the Web3 AI Agent Ecosystem

MCP is rapidly becoming a key component of the Web3 AI Agent ecosystem. With a plugin-like architecture and the introduction of the MCP Server, it provides new tools and capabilities for AI Agents. Similar to other emerging concepts in the Web3 AI space, MCP (which stands for Model Context Protocol) originated from Web2 AI and is now being reimagined in the Web3 environment.

The Essence and Importance of MC

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

The core limitations faced by current large language models include:

• Unable to browse the internet in real-time
• Cannot directly access local or private files
• Cannot autonomously interact with external software

MCP acts as a universal interface layer to fill these capability gaps, enabling AI Agents to utilize various tools. MCP can be likened to a unified interface standard in the AI application domain, making it easier for AI to connect with various data sources and functional modules.

This standardized protocol is beneficial for both parties:

• AI Agent (client) can securely connect to external tools and real-time data sources.
• Tool developers (server side) can achieve one-time integration and cross-platform usage.

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

Differences Between MCP and Traditional APIs

The design of APIs is primarily aimed at humans rather than being 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 documentation and must be hard-coded to adapt to each type of API (such as REST, GraphQL, RPC, etc.).

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

Recently, a certain cloud service platform announced that developers can directly deploy remote MCP servers on its platform with minimal device configuration. This greatly simplifies the deployment and management process of MCP servers, including authentication and data transmission, and can be called "one-click deployment".

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 real-time on-chain 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 connected, 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-style architecture to seamlessly integrate third-party plugins and tools. As a result, new AI Agent infrastructure and applications based on the MCP and A2A protocols are emerging, specifically designed for Web3 scenarios, enabling Agents to access multi-chain data and interact natively 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 MCP servers.
• Provide MCP aggregator and micropayment features to lower the usage threshold.

DeepCore

DeepCore also offers an MCP Server registration system, focusing on the cryptocurrency field, and further expands to 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 tool access capabilities for Agents
• A2A: Provides agents with the ability to collaborate with each other.

The Combination of Blockchain and MCP Server

The integration of blockchain technology in MCP Server has multiple benefits:

1. Obtain long-tail data through an encrypted native 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 Agents.
3. Introduce a staking/penalty mechanism, combining an on-chain reputation system to build the trust system of the MCP server.
4. Improve 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 publish sources like ESG data, enriching ecological diversity.

Future Trends and Industry Impact

More and more people in the cryptocurrency 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, and more, forming a more efficient Agent service economy empowered by cryptocurrency and blockchain as a medium.

The true value and potential of MCP can only be truly seen when AI Agents integrate it and transform it into practical applications. Ultimately, Agents are the carriers and amplifiers of MCP's capabilities, while blockchain and cryptographic mechanisms build a trustworthy, efficient, and composable economic system for this intelligent network.