MCP and AI Agent: A New Framework for Artificial Intelligence Applications

1. Introduction to MCP Concept

In the field of artificial intelligence, traditional chatbots often lack personalization and proactivity. To address this issue, developers have introduced the concept of "persona," endowing AI with specific roles and personalities. However, this still has not made AI a proactive task executor. The Auto-GPT project was born, allowing AI to automatically perform tasks based on predefined rules and tools.

Although Auto-GPT has achieved a certain degree of autonomous execution of AI, it still faces issues such as inconsistent tool invocation formats and poor cross-platform compatibility. MCP (Model Context Protocol) was created to simplify the interaction between AI and external tools. By defining standardized interfaces and communication specifications, MCP significantly simplifies the interaction process between AI models and external tools, improving development efficiency.

2. Collaboration between MCP and AI Agent

MCP and AI Agent complement each other. The AI Agent primarily focuses on automation operations in blockchain, smart contract execution, and crypto asset management, while MCP emphasizes simplifying the interaction between the AI Agent and external systems by providing standardized protocols and context management.

MCP provides a unified communication standard for AI Agents to interact with external tools (including blockchain data, smart contracts, off-chain services, etc.). This standardization addresses the issue of fragmented interfaces in traditional development, enabling AI Agents to seamlessly connect with multi-chain data and tools, significantly enhancing their autonomous execution capabilities. For example, DeFi AI Agents can obtain market data in real-time and automatically optimize their investment portfolios through MCP.

In addition, MCP has opened up new directions for AI Agents, namely, collaboration among multiple AI Agents. Through MCP, AI Agents can collaborate with functional divisions to jointly complete complex tasks such as on-chain data analysis, market forecasting, and risk control management, enhancing overall efficiency and reliability. In terms of on-chain trading automation, MCP connects various trading and risk control Agents, helping to address issues such as slippage, trading friction, and MEV in trading, achieving safer and more efficient on-chain asset management.

3. Related Projects

1. DeMCP

DeMCP is a decentralized MCP network dedicated to providing self-developed open-source MCP services for AI Agents, offering a deployment platform for MCP developers to share commercial profits, and achieving one-stop access to mainstream large language models (LLM). Developers can access services by supporting stablecoins.

2. DARK

DARK is an MCP network built on Solana in a trusted execution environment ( TEE ). Its first application is under development, aiming to provide efficient tool integration capabilities for AI Agents through TEE and MCP protocols, allowing developers to quickly access various tools and external services with simple configurations.

3. Cookie.fun

Cookie.fun is a platform focused on AI Agents within the Web3 ecosystem, providing AI Agent indices and analytical tools. The platform helps users evaluate the performance of different AI Agents by showcasing metrics such as their cognitive influence, intelligent following capability, user interaction, and on-chain data. Recently, the Cookie.API 1.0 update launched a dedicated MCP server, providing plug-and-play MCP services for developers and non-technical personnel.

4. SkyAI

SkyAI is a Web3 data infrastructure project built on the BNB Chain, aimed at constructing blockchain-native AI infrastructure by extending MCP. The platform provides a scalable and interoperable data protocol for Web3-based AI applications, intending to simplify the development process and promote the practical application of AI in blockchain environments through the integration of multi-chain data access, AI agent deployment, and protocol-level utilities.

4. Future Outlook

The MCP protocol, as a new narrative of the fusion between AI and blockchain, demonstrates immense potential in enhancing data interaction efficiency, reducing development costs, and strengthening security and privacy protection, particularly in decentralized finance scenarios where it has broad application prospects. However, most current projects based on MCP are still in the proof of concept stage and have not yet launched mature products, leading to a trust crisis in the market regarding these projects.

In the future, the development of the MCP protocol faces multiple challenges, including accelerating product development progress, ensuring a close connection between tokens and actual products, enhancing user experience, and resolving technical integration issues. Nevertheless, the MCP protocol still shows great market development potential. With the continuous advancement of AI technology and the gradual maturity of the MCP protocol, it is expected to achieve broader applications in areas such as DeFi and DAO in the future.

The MCP protocol, as an important auxiliary force in the integration of AI and blockchain, is expected to become a key engine driving the development of the next generation of AI agents. However, achieving this vision still requires addressing challenges in areas such as technical integration, security, and user experience. As these issues are gradually resolved, the MCP protocol will play an increasingly important role in the fusion of AI and blockchain.