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

1. Introduction to MCP Concept

Traditional chatbots in the field of artificial intelligence often lack personalization and proactivity. To address this issue, developers introduced the concept of "persona," giving AI specific roles and personalities. However, even so, AI remains a passive responder. To enable AI to proactively perform tasks, the Auto-GPT project was born. This project allows for the definition of tools and functions for AI, enabling it to automatically execute tasks based on predefined rules.

Despite Auto-GPT achieving a certain degree of autonomous execution of AI, it still faces issues such as non-unified tool invocation formats and poor cross-platform compatibility. In response to these challenges, MCP (Model Context Protocol) has emerged. MCP aims to simplify the interaction between AI and external tools by providing a unified communication standard, enabling AI to easily invoke various external services. By defining standardized interfaces and communication specifications, MCP significantly simplifies the interaction process between AI models and external tools, improving development efficiency.

2. The Synergistic Effect of MCP and AI Agent

The relationship between MCP and AI Agent is complementary. The AI Agent primarily focuses on automation operations in the blockchain, execution of smart contracts, and management of crypto assets, emphasizing privacy protection and integration of decentralized applications. On the other hand, MCP focuses on simplifying the interaction between the AI Agent and external systems, providing standardized protocols and context management, enhancing cross-platform interoperability and flexibility.

The core value of MCP lies in providing a unified communication standard for the interaction between AI agents and external tools (such as blockchain data, smart contracts, off-chain services, etc.). This standardization addresses the issue of fragmented interfaces in traditional development, allowing AI agents to seamlessly connect with multi-chain data and tools, significantly enhancing their autonomous execution capabilities. For example, DeFi-type AI agents can access market data in real-time and automatically optimize their investment portfolios through MCP.

In addition, MCP has opened up a new collaborative direction for AI Agents. Through MCP, multiple AI Agents can collaborate based on functional division of labor to jointly complete complex tasks such as on-chain data analysis, market forecasting, and risk management, enhancing overall efficiency and reliability. In terms of on-chain trading automation, MCP can connect various trading and risk control Agents to address issues such as slippage, transaction wear, and MEV, achieving safer and more efficient on-chain asset management.

3. Introduction to 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 that shares commercial profits with MCP developers 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, operating under the trusted execution environment (TEE). Its first application is currently under development, aiming to provide efficient tool integration capabilities for AI Agents through TEE and the MCP protocol, 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 users with comprehensive AI Agent indices and analytical tools. The platform showcases metrics such as the mental influence of AI Agents, their intelligent following capabilities, user interactions, and on-chain data, helping users assess the performance of different AI Agents. Recently, Cookie.fun launched a dedicated MCP server, offering plug-and-play MCP services specifically for agents.

4. SkyAI

SkyAI is a Web3 data infrastructure project built on the BNB Chain, aimed at constructing blockchain-native AI infrastructure by extending the MCP. The platform provides a scalable and interoperable data protocol for Web3-based AI applications, with plans to simplify the development process through the integration of multi-chain data access, AI agent deployment, and protocol-level utilities. Currently, SkyAI supports aggregated datasets from BNB Chain and Solana, and in the future, it will also support MCP data servers from the Ethereum mainnet and Base chain.

Four, Future Development Outlook

The MCP protocol, as a new narrative of the integration of AI and blockchain, shows great potential in enhancing data interaction efficiency, reducing development costs, and improving security and privacy protection, especially in decentralized finance and other scenarios. However, most current projects based on MCP are still in the proof-of-concept stage and have not yet launched mature products, reflecting a crisis of trust in the market for MCP projects.

Accelerating product development, ensuring a close connection between tokens and actual products, and enhancing user experience are the core issues currently faced by the MCP project. In addition, the promotion of the MCP protocol in the crypto ecosystem still faces challenges in technical integration, requiring significant development resources to unify the smart contract logic and data structures across different blockchains and DApps.

Despite facing challenges, the MCP protocol itself 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. For example, AI agents can obtain on-chain data in real-time through the MCP protocol, execute automated trades, and enhance the efficiency and accuracy of market analysis.

The decentralized nature of the MCP protocol is expected to provide a transparent and traceable operating platform for AI models, promoting the decentralization and assetization of AI assets. As an important auxiliary force in the integration of AI and blockchain, the MCP protocol is expected to become a key engine driving the next generation of AI Agents. However, achieving this vision still requires addressing various challenges in technology integration, security, and user experience.