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A new paradigm for AI interaction: MCP (Model Context Protocol) scenario-based applications and popular science

Written by
Audrey Miles
Updated on:July-11th-2025
Recommendation

AI interaction has ushered in a revolutionary breakthrough, and the MCP protocol has created a new workflow collaboration model.

Core content:
1. The innovative concept and core value of the Model Context Protocol (MCP)
2. How MCP serves as a bridge to connect AI and external tools to achieve automated workflows
3. Typical application cases of MCP in the fields of intelligent programming, document processing, and data analysis

Yang Fangxian
Founder of 53AI/Most Valuable Expert of Tencent Cloud (TVP)

Preface

When the wave of AI big models swept in, we were pleasantly surprised by its powerful language understanding and generation capabilities, but we were often limited by the inefficiency and fragmentation of traditional interaction methods. How can we truly integrate AI into our workflow and efficiently collaborate with various tools and services?  The birth of the Model Context Protocol (MCP)  is to break this bottleneck and build a new paradigm for AI interaction. This article will explain MCP to you in an easy-to-understand way, reveal its scenario-based applications, and provide a comprehensive popular science guide to help you appreciate the charm and potential of MCP.

1. MCP: A bridge connecting AI and the world

What is MCP?

MCP, the full name of  Model Context Protocol , is  an innovative technology released by Anthropic (the creator of Claude AI) in open source at the end of 2024. Simply put, MCP is a set of standardized protocols that acts like a universal "translator" that enables large AI models to "talk" to various external tools and services in a unified and efficient way .

MCP's Core Values

  • Standardized interaction:  MCP defines a set of common message formats and interaction processes, breaking down the barriers between different AI models and tools and achieving true "cross-platform" collaboration.

  • Automated workflow:  Through MCP, AI can automatically access and operate external tools without human intervention, greatly improving work efficiency.

  • Scenario-based application expansion:  The standardized characteristics of MCP provide unlimited possibilities for the application of AI in various scenarios, such as programming assistance, data analysis, intelligent assistants, etc.

  • Open ecosystem construction:  The open source nature of MCP encourages developers to jointly build a rich MCP Server tool ecosystem to accelerate AI application innovation.


2. Scenario-based applications of MCP: empowering all industries

The power of MCP lies in its wide applicability. It can be applied to various scenarios that require the collaboration of AI and external tools. Here are a few typical application cases:

  1. AI Coding Assistant


  • Scenario description:  When developers write code in an IDE, they need an AI assistant to understand the code context and perform operations such as code generation, error detection, and code refactoring.

  • MCP Application:  Using MCP Server, AI assistants can directly access the IDE's file system, editor status, and even browser debugging tools to achieve deeper code understanding and smarter auxiliary functions. For example, AI programming tools such as Cline and Cursor have taken the lead in supporting the MCP protocol.

  • Intelligent Document Processing


    • Scenario description:  Enterprises need AI to automatically process large amounts of documents, such as contract review, financial statement analysis, knowledge base construction, etc.

    • MCP application:  Through MCP Server, AI can directly access file systems, databases, cloud storage, etc., automatically read, analyze, and extract document information, and complete corresponding business processes.

  • Intelligent Data Analytics


    • Scenario description:  Data analysts need AI assistants to connect to various data sources to perform data cleaning, data visualization, data mining, etc.

    • MCP application:  With the help of MCP Server, AI can connect to databases, data warehouses, API interfaces, etc., automatically obtain data, and use various data analysis tools for in-depth analysis to provide strong support for decision-making.

  • Intelligent Knowledge Assistant


    • Scenario description:  Users need AI assistants to quickly retrieve information, integrate knowledge, and complete complex tasks, such as writing research reports, travel planning, and schedule management.

    • MCP Application:  Combined with MCP Servers such as browsers, search engines, calendars, and emails, AI assistants can become all-round assistants and efficiently complete complex tasks such as information collection, knowledge integration, and task execution.

    3. MCP User Guide: From Getting Started to Practice

    Quick Start with MCP

    1. Choose an AI client that supports MCP:  Currently, the clients that support MCP mainly include Cline (open source and free), Cursor, Windsurf, Claude App, etc. This article recommends using the open source and free  Cline  for a beginner experience.

    2. Install VS Code editor:  Cline is a VS Code plug-in, you need to install VS Code editor first.

    3. Install the Node.js runtime environment:  MCP Server is usually developed based on Node.js or Python, and the corresponding runtime environment needs to be installed.

    4. Install MCP Server tools:  You can choose existing MCP Server tools in the Cline plug-in market, such as GitHub MCP Server, File System MCP Server, etc., or you can customize and develop MCP Server according to your own needs.

    Practical Exercise: File System MCP Server - Let AI Understand Your Computer

    To help you better understand the practical application of MCP, we take  File System MCP Server  as an example to teach you how to deploy and configure a runnable case so that AI can read the local file directory structure of your computer.

    Preparation

    • Install an AI client that supports the MCP protocol: Cline (open source and free, recommended) or Cursor.
    • Install the VS Code editor.
    • Install the Node.js runtime environment.

    Practical steps:

    1. Create the mcp.json configuration file

{
  "mcpServers": {
    "filesystem": {
      "command": "cmd",
      "args": [
        "/c",
        "npx",
        "-y",
        "@modelcontextprotocol/server-filesystem"
      ],
      "@modelcontextprotocol/server-filesystem": {
        "allowedPaths": [
          "C:\\Users\\your username\\Desktop" // Replace with your desktop path
        ]
      }
    }
  }
}

Notice:

    • Please replace "C:\Users\yourusername\Desktop" with the actual desktop path on your computer. Windows system paths require double slashes \.
    • The allowedPaths field defines the directories that the File System MCP Server is allowed to access. Here we set it to the desktop directory. You can modify it according to your actual needs.
    • In your project root directory, create a folder called .cursor (skip if it already exists).
    • Inside the .cursor folder, create a file named mcp.json.
    • Copy and paste the following JSON code into the mcp.json file:

  1. Start File System MCP Server

    • Open the VS Code editor and make sure the Cline plugin is installed and enabled.
    • Click the Cline icon in the status bar at the bottom of VS Code to open the Cline chat window.
    • In the Cline chat window, enter any command (such as "Hello") to activate the Cline AI assistant.
    • Click the "gear" icon in the upper right corner of the Cline chat window to enter the Cline settings interface.
    • On the left side of the settings interface, click the "MCP" tab.
    • In the “MCP Servers” panel, you should see the “filesystem” MCP Server automatically loaded by Cline.

    • Important:  At this time, Cline will automatically pop up a black command line window. Please do not close this window , as it is running the File System MCP Server service.

    • If the "filesystem" MCP Server is not automatically enabled, click the "Enable" switch to its right to enable it manually.

  2. Testing the File System MCP Server

    3. List files and folders on the desktop
      • Cline AI Assistant will recognize that you want to use File System MCP Server and request authorization. Click the “Approve” button to authorize.
      • Wait a moment, and the Cline AI assistant will return a list of files and folders on your desktop. Congratulations, the File System MCP Server has been deployed successfully!
      • In the Cline chat window, enter the following command:

      Advanced practice: Let AI help you organize desktop files

      Now you can try more complex instructions, such as:

      • "Move all the image files on my desktop into a folder called 'Images'"

      • "Create a text file named 'Notes' on the desktop with the content 'Learned the MCP protocol today'"

      Through File System MCP Server, the AI ​​assistant can efficiently complete various file management tasks just like operating local files, greatly improving your work efficiency.

      4. Advanced practical exercises: WindSurf + File System MCP Server - Multiple client options

      In addition to Cline,  WindSurf  is also an excellent AI client that supports the MCP protocol, especially suitable for users who need multi-platform and multi-device collaboration. This section will demonstrate how to use  the WindSurf  client in conjunction with  the File System MCP Server to enable AI to access the local file system across platforms.

      Preparation 

      • Install an AI client that supports the MCP protocol: Cline or  WindSurf (recommended, you have to pay for it) .

      • Install the VS Code editor (optional, for editing configuration files).
      • Install the Node.js runtime environment.

      • Install the WindSurf client:  Visit the WindSurf official website  https://windsurf.ai/ [1]  to download and install the WindSurf client (supports multiple platforms such as Windows and macOS).

      Practical steps:

      1. Create the mcp.json configuration file

      {
          "mcpServers": {
              "filesystem": {
                  "command": "npx",
                  "args": [
                      "-y",
                      "@modelcontextprotocol/server-filesystem",
                      "/Users/XXX/Desktop",
                      "/Users/XXX/Desktop/XXXX"
                  ]
              }
          }
      }

      Notice:

        • Be sure to replace "C:\Users\yourusername\Desktop" with the actual desktop path on your computer. Windows system paths require double slashes \.
        • The allowedPaths field defines the directories that the File System MCP Server is allowed to access. Here we set it to the desktop directory. You can modify it according to your actual needs.


      1. Configuring WindSurf Client


        • Open the WindSurf client application (desktop or mobile).
        • Click the “Configure MCP” button.
        • Copy and paste the above mcp.json content into it
        • Click the “Save” or “Save” button to complete the WindSurf client configuration.


      2. Testing WindSurf + File System MCP Server

        WindSurf, please list the files on my desktop

        Or more concisely:

        Desktop file list


        • WindSurf AI Assistant will recognize that you want to use File System MCP Server and ask for authorization. Click the “Allow” or “Allow” button to authorize.
        • Wait a moment and the WindSurf AI Assistant will return a list of files and folders on your desktop.
        • In the WindSurf client chat window, enter the following command:

        Advanced Practice: WindSurf Mobile Cross-Platform File Access

        WindSurf's cross-platform feature allows you to access the local file system on your computer anytime and anywhere through the WindSurf client on your mobile phone or other devices, realizing true mobile office and data interconnection.

        For example:

        • In the WindSurf client on your mobile phone, enter the command "WindSurf, help me open the 'work plan.docx' file on the desktop" to preview the document content on the computer desktop on your mobile phone.
        • In the tablet WindSurf client, enter the command "WindSurf, compress and package all the pictures in the desktop 'Images' folder" to remotely control the computer to compress files.

        V. MCP Learning Resources: In-depth Exploration and Continuous Improvement

        • MCP official GitHub repository: https://github.com/modelcontextprotocol/modelcontextprotocol [3]  (authoritative information for in-depth understanding of the MCP protocol) 

        • Smithyery.ai: https://smithery.ai/ [4]  (Explore the rich MCP Server tool ecosystem) 

        • Cline plugin:  (Search "Cline" in the VS Code plugin market) (Quickly experience the powerful functions of MCP)

        • Cursor Editor: https://cursor.sh/ [5]  (AI programming tool integrated with MCP) 

        • MCP official documentation : https://modelcontextprotocol.io/quickstart/client [6]

        • MCP Server Navigation: https://mcp.so/ [7] (Explore the rich MCP Server tool ecosystem)

        • MCP Server Navigation: https://mcps.live/ [8] (Explore the rich MCP Server tool ecosystem)

        • Important development trends of AI: MCP technology popularization: https://xiangyangqiaomu.feishu.cn/wiki/PXAKwEgLQir9rkkV1zjcGnMHntg?from=from_copylink [9]

        6. MCP tool recommendation: Creating personalized AI workflows

        • Browser Tools MCP:  Essential for front-end development, allowing AI to easily understand and manipulate web content.

        • File System MCP:  A powerful file management tool that allows AI to automatically process local files.

        • GitHub MCP:  A code management tool that allows AI to assist in code repository operations.

        • Sequential Thinking MCP:  Improves AI’s reasoning ability and enables AI to better solve complex problems.

        • Time MCP:  A time management assistant that allows AI to easily perform time conversion and scheduling.

        Conclusion

        The emergence of MCP marks a new stage of development for AI applications. It breaks down the barriers between AI and the outside world, making AI a real intelligent assistant in our work and life. Embrace MCP, explore its infinite possibilities, and welcome the AI-driven future together!

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