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This week, just reaching the middle, can be defined as an exhilarating week. Since the weekend, I have been on a roller coaster ride in the crypto world every day, and I am now numb from the drops. Just as I was healing from the brutal PVP of Sol, CZ and Heyi, along with a group of KOLs, started a frenzy, from "mubarak" to "Mashallah," from a community-driven meme contest to He Yi and CZ personally getting involved in the fun. This celebration not only created several meme coins with market values in the tens of millions of dollars but also left me, a small player in the meme game, with new wounds before the old ones had healed. If all goes well, the Middle Eastern narrative will soon cool down, but what remains on the BNB Chain will not only be the volatile K-lines. Teams that truly understand community needs, such as TUT, which lowers development barriers through tutorial videos, may be the ones to reap the final fruits. As I delved deeper into crypto AI research, I discovered an interesting protocol, MCP, or Model Context Protocol, an open standard developed by Anthropic in December 2024, which caught my attention.
What is MCP? How is it related to AI Agents?
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MCP (Model Context Protocol) is a new open standard protocol designed to establish secure bidirectional links between large models and data sources, primarily addressing the issue of data acquisition (data silos). In AI project development, it is evident that integrating AI models is complex, and existing frameworks like LangChain Tools, LlamaIndex, and Vercel AI SDK have their issues. LangChain and LlamaIndex have high code abstraction and heavy commercialization; Vercel AI SDK is too deeply tied to Next.js. The goal of MCP is to connect AI assistants with data sources such as content libraries, business tools, and development environments. Its foundation can be traced back to a release in November 2024, aimed at helping AI models generate more relevant and accurate responses. The technical architecture is shown in the diagram below:
Is MCP the "Digital Nervous System" of AI Agents?
You might ask, "Is MCP necessary?" The answer is: it is possible, but particularly troublesome. Without MCP, every time an AI agent wants to connect to a new data source (like a new exchange), programmers have to write code from scratch, just like having to solder a plug every time you want to use a new appliance. With MCP, it’s like giving the AI agent a "universal plug" that can be used anywhere, saving time and effort. MCP is like a USB-C unified charging interface, standardizing the connection of AI to everything. Non-technical users can also connect smart home devices to AI through MCP (like controlling smart bulbs with Slack commands), and it also reserves multimodal interfaces for future connections to new devices like AR glasses and brain-computer interfaces. Therefore, MCP itself is merely a tool similar to a nervous system, plug-and-play to read target data models, process and analyze them, and ultimately generate the expected answers.
Core Applications of MCP: Examples for Illustration
This article will not introduce complex terminology; instead, I will provide a relatable example.
AI Agent: From "Q&A" to "Execution"
Scenario 1: Want to watch a movie on the weekend
Traditional AI: "What cinemas are nearby?" (requires manual input of location)
MCP+AI: "Open the local map application, search for cinemas within 5 kilometers, filter for IMAX screenings, and send the ticket purchase link to WeChat" (fully automated operation)
Scenario 2: Stock investment
Traditional AI: "I suggest buying XX stock" (possibly based on outdated data)
MCP+AI: Real-time fetching of exchange data + macroeconomic indicators + news sentiment, generating an encrypted investment report through zero-knowledge proof to provide current stock trading options.
"Practical" Examples of MCP in the Crypto World
Let’s see how MCP and AI agents "perform" in cryptocurrency:
- Helping you seize investment opportunities
You ask the AI agent, for example, $AIXBT: "Is it a good time to buy Ethereum?" It connects to the exchange via MCP, finds that the price of Ethereum is rising, then connects to Twitter, sees everyone praising it, and immediately responds: "Now is a great time to buy!" This is like asking a friend whether to eat at a certain restaurant, and they check the reviews before telling you.
- Automatically helping you make money
You tell the AI agent: "Buy when Bitcoin drops to $50,000." It uses MCP to monitor the exchange price, and once it drops to $50,000, it immediately places an order. This is like setting an alarm clock that wakes you up when the time comes.
- Telling you which coin is the hottest
The AI agent scans social media through MCP, discovers that "mubarak" has been mentioned a million times today, and can also combine exchange data to tell you its trading volume is surging, reminding you: "This coin might take off!" This is like a friend telling you which movie is super popular right now, prompting you to buy tickets quickly.
- Protecting your wallet's security
When handling private keys or transactions, MCP can also encrypt data to ensure that hackers cannot steal your information, just like your credit card number is not leaked when shopping online.
MCP and Crypto AI Agents
There is no competitive relationship between the MCP protocol and crypto AI agents. On the contrary, MCP provides the necessary data connection support for crypto AI agents, enabling them to complete tasks more efficiently. In the cryptocurrency ecosystem, MCP and crypto AI agents have a cooperative relationship, jointly promoting the application and development of AI technology in this field.
MCP: Responsible for providing standardized data access interfaces, serving as an infrastructure-level protocol.
Crypto AI Agents: Responsible for processing data and executing specific tasks, serving as application-level programs.
Looking Ahead
MCP shows great potential in crypto AI agents by connecting them with real-time data, enhancing market analysis, automated trading, and secure data processing. Despite facing challenges, MCP may see broader adoption in the future, shaping a smarter cryptocurrency ecosystem. For instance, existing crypto AI agents like AIXBT, Kaito, BNKR, etc., can adopt MCP as part of their tech stack, significantly reducing development costs and improving product efficiency. However, this may lead to a loss of their unique characteristics and features. Some crypto analysts claim that the recent surge of Manus + MCP is the key to the impact on web3 AI agents. I have a different perspective. Simply put, web3 AI agents are the front end equipped with AI algorithms, while MCP is the transmitter; the core data and models are where the true value lies. Manus is like a large supermarket that may have everything, with many users, but many are standard products that may not meet the diverse needs of users. In contrast, current web3 AI agents are like specialized stores, able to provide users with more professional and higher value-added products and services. As I mentioned at the beginning, those teams that truly understand user needs and delve deeper may be the ones to reap the final fruits.**
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