MCP: The Catalyst for AI's Next Big Leap - And Why You Can't Afford to Miss It

by Anthony Law    2025-04-29

In the world of artificial intelligence, while the dream of achieving Artificial General Intelligence (AGI) still seems far off, a significant development has already arrived: the Model Context Protocol, or MCP. Think of MCP as the "USB for large language models (LLMs)." Just as USB-C standardized communication between devices, MCP uses a standardized interface to seamlessly connect LLMs with external data and tools. It does this through a client-server architecture and the JSON-RPC protocol, integrating models with resources like file systems, databases, and API services. This enables AI systems to access real-time data and tools, greatly reducing the problem of "hallucinations" caused by a lack of information.

Benefits for Businesses and Governments

• Low-Cost Standardized Access: Traditional companies don't need to rebuild their existing systems. They can simply expose data interfaces through an MCP server, allowing AI models to directly use local resources such as order databases or customer management systems. This lowers the technical barrier to entry.
• Security and Control: MCP supports local deployment, so sensitive data doesn't have to be sent to the cloud. This meets government regulations on data privacy.

MCP: Going Beyond Just Conversations

Search engine enhanced LLMs like Perplexity.ai have shown the way forward in AI. When models can dynamically use search engines like Google or Bing, they're no longer limited by the historical data they were trained on. For example, asking for the latest 2024 Olympics medal table, Perplexity.ai can give accurate results by retrieving information from reliable media sources in real-time. This marks the first step of LLMs moving from "static knowledge bases" to "dynamic information agents."

However, MCP takes things even further. It doesn't just solve the problem of information timeliness; it expands the capabilities of LLMs from just retrieving answers to performing real-world actions. Through its standardized protocol, MCP allows LLMs to directly access three key types of resources:

• Dynamic Data Sources: Such as stock exchange APIs, IoT sensors, and government open data platforms.
• Business Systems: Like ERP, CRM, and supply chain management software.
• Physical Devices: Including robotic arms in smart factories, medical imaging devices, and urban traffic lights.

With MCP, LLMs can become all-purpose assistants. When companies use natural language to manage global supply chains, entire industries could be transformed. And when governments use it to run cities, smart cities will evolve to a whole new level.

Transforming Workflows: The Case of Training Institutions

Take a training institution as an example. Traditionally, managing teacher schedules, student bookings, and course material distribution required using multiple systems like Google Calendar, Excel, and email clients. But with an AI assistant integrated through MCP, these processes can be automated:

• Schedule Optimization: The AI checks the teachers' free time and students' needs in the database and automatically creates a class schedule, then sends it to the calendar system via MCP.
• Resource Distribution: Based on the course topic, the AI fetches teaching materials from the file server (accessed through MCP) and sends them to students via email or chat tools.
• Exception Handling: If a teacher takes leave, the AI finds a substitute and notifies the students, all through natural language interaction, without the need for manual operation of complex interfaces.

This brings two main benefits:

• No Learning Curve: Employees just describe what they need in normal language, and the AI takes care of the rest.
• Fewer Errors: MCP ensures data accuracy by getting information directly from the database, reducing mistakes caused by human input.

MCP-Driven Cost Revolution in Business Collaboration

When companies connect with customers, suppliers, and partners using MCP, business processes can be automated. For instance:

• Supply Chain Management: Retail companies' AI can automatically place restocking orders with suppliers. MCP connects the inventory database with the suppliers' APIs to compare prices and stock levels in real-time.
• Cross-Platform Payments: Government public service platforms can integrate banking and tax systems via MCP, allowing citizens to pay bills and file reports through a chat interface.

There are significant cost advantages:

• Low Adaptation Cost: Existing systems only need to develop an MCP server interface, cutting the development time by 70% without major overhauls.
• Ecosystem Reuse: There are over 3,000 open source MCP servers on GitHub, covering various sectors like finance, education, and healthcare. Companies can use these ready-made solutions.

MCP: A Strategic Opportunity for Smart Cities

For Hong Kong, aiming to become a smart city leader, MCP can enable the following:

• Traffic Improvement: By combining real-time subway and bus data with AI models, MCP can adjust route planning to reduce congestion.
• Government Services: Citizens can ask about policies in natural language, and the AI will use MCP to access relevant law databases and case libraries for accurate answers.
• Inter-departmental Cooperation: Medical, fire, and police systems can share data via MCP, improving emergency response. For example, it can quickly dispatch the nearest resources during a fire.

To make this happen:

• Standardize MCP: The government should lead the way in creating MCP standards for public data interfaces and encourage businesses to join the ecosystem.
• Support Small and Medium-Sized Enterprises: Provide financial help to traditional companies so they can easily adopt MCP.

In conclusion, MCP is essential for digital transformation. It's a powerful tool for businesses to cut costs and increase efficiency, and a foundation for governments to build smart cities. As major players like Alibaba Cloud and Inspur are rapidly developing the MCP ecosystem, companies and cities that ignore it may fall behind in the AI era. Just as the internet relies on the HTTP protocol, MCP will be the backbone of future intelligent societies.

What to Do Now

• For Businesses: Evaluate how well your existing systems can work with MCP, and start with processes that are used frequently and cost a lot in terms of manpower.
• For Governments: Set up MCP pilot projects, such as smart government service halls, to test the technology and gain experience.