Can the MCP that connects everything, combined with Web3, become the next wave of AI hundredfold narrative?

This article delves into the combination of Web3 and MCP (Model Context Protocol), analyzes how MCP acts as a "universal plug" to seamlessly connect AI with the blockchain world, and introduces related application projects and future development directions. (Synopsis: DA Labs reveals the secret of Binance's "hot and cold wallet transfer" predicts the hidden signal of meme coins) (Background supplement: DA Labs Research Report" Abstract ecology must play three chain games, quickly accumulate XP ambush airdrop points) Since AI Agent formed a wave of incremental narratives in the crypto market last year, many people are speculating about where the next hyped AI hotspot will be sacred, and MCP, which has recently received a lot of attention in the Web2 AI circle, is one of the directions suitable for focus. The pain point of Web3's AI in the past was that models could not seamlessly access the data of the blockchain world, and blockchain applications could not take full advantage of the capabilities of AI. But the emergence of the MCP (Model Context Protocol) open standard protocol provides an elegant solution to this problem. MCP was developed by Anthropic, the big language model Claude, which breaks the "data island" dilemma that has long plagued many developers, and creates new possibilities for the deep combination of AI and blockchain. This article will explore how the MCP protocol works in the Web3 world, what projects are currently exploring this area, and where it might go in the future. Web2 MCP related application summary (Source:a16z) MCP: The "universal plug" of large models Before discussing the combination of MCP and Web3, we need to understand what MCP really is. In simple terms, MCP is an open standard protocol that allows large language models (LLMs) to integrate seamlessly with external data sources and tools. To use a life-like metaphor, MCP is like a "universal plug" that allows AI models to connect to a variety of different services and systems. In traditional AI application development, whenever an AI model needs to be wired to a new data source or tool, developers need to write specialized code to make that connection. It's like needing to solder a new plug every time you want to use a new appliance. The emergence of MCP is like standardizing electrical plugs, allowing any AI model to access various services through this standard interface. MCP's technical architecture consists of three main components: MCP client: typically an AI assistant or interface, such as a Claude Desktop or Cursor editor. MCP Server: A service that provides specific functions, such as querying data, executing transactions, or interacting with smart contracts. MCP protocol: Defines the standard way of communication between a client and a server. This architecture makes MCP highly scalable and suitely. An MCP client can connect to multiple MCP servers, and an MCP server can be used by multiple clients. For example, you can use Claude Desktop, an MCP client, to install different MCP servers that allow it to query the blockchain information you want to know, transfer tokens, and even deploy smart contracts. MCP Apps in the Web3 World The complexity of the Web3 ecosystem has always been a chasm that is difficult for the average user to cross. From choosing the right wallet, understanding the Gas fee mechanism, to participating in on-chain operations, and so on, each step requires prior knowledge. The emergence of MCP is a great tool to change this situation, and here are two application directions: Smart wallet management and cross-chain operation Traditionally, managing multi-chain assets requires the use of different wallets and interfaces, and switching is costly and error-prone. MCP's integrated smart wallet system aggregates multi-chain assets through a single interface, enabling users to optimize asset allocation in a conversational manner. For example, when a user asks, "How should the portfolio be optimized?" The MCP-driven system can analyze the current asset distribution and provide corresponding and customized asset allocation recommendations taking into account the current market conditions, users' risk appetite, and even the trend of on-chain data. The system also helps users understand the logic behind these recommendations, making the decision-making process more transparent. This application direction is particularly suitable for single-interface products such as UniversalX that use chain abstraction technology, which can enrich the layers of products. Adaptive DeFi Engagement Model The barrier to entry in the DeFi ecosystem has always been high – users need to understand complex concepts such as borrowing rates, impermanent losses, collateral ratios, and more. The advent of MCPs creates the possibility of "adaptive engagement," meaning that the system automatically adjusts the complexity of the interface based on the user's level of experience, risk tolerance, and financial goals. For DeFi novices, the system offers simplified operating options and detailed risk descriptions; For veterans, the system offers advanced strategy options and in-depth market analysis. This adaptive approach allows everyone from novice to professional traders to get the experience that suits them best. Web3 and MCP-related projects APRO APRO is one of the most comprehensive projects for Web3 and MCP applications, and the goal of the project is to create a complete solution from data security to real-time verification. Unlike projects that simply provide MCP servers, APRO's technical architecture is multi-layered: Framework layer: Cooperate with DeepSeek, ElizaOS, Virtuals, etc. to provide development support for AI agents Technology layer: Combine BNB Greenfield, Phala Network, Mind Network and other key technologies to build a security infrastructure Protocol layer: through ATTPs and AI Oracle Creating a Trusted Data Pipeline APRO's dual-engine architecture, ATTPs and AI Oracle, is one of the key moats of their portfolio. ATTPs (Agent Text Transfer Protocol Secure) is the world's first blockchain-based AI data transfer protocol, which ensures that data is not tampered with and verifiable through multi-layer verification mechanisms (zero-knowledge proof, Merkle tree, blockchain consensus). AI Oracle, as LLM's "real-time fact-checker", solves the pain point that large models such as GPT cannot obtain real-time trusted information. Another advantage of APRO is its combination with BNB Greenfield. BNB Greenfield is a decentralized storage network where you can freely create, store and exchange data, and seamlessly integrate with BNB Smart Chain to return data rights to users. Seeing this, you should imagine the application of APRO plus BNB Greenfield: AI Oracle collects data from multiple sources→ encrypts ATTPs and transmits the data to Greenfield for storage. There are three key capabilities: Decentralized data storage: All raw data is stored directly on Greenfield,...