MCP cover image
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2025-03-21

A Simple Model Context Server (MCP) For AI Usecases

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MCP (Model Context Protocol)

by Gaurav Kabra

The Model Context Protocol (MCP) is a standardized way, introduced by Anthropic, for LLMs to interact with external tools and functions and injecting context in LLMs. It allows models to:

  • Request real-time information
  • Execute actions in external systems
  • Access specialized knowledge
  • Interact with APIs and services

→ Agents → MCP The 2nd figure is like this:

So we improve and get to the 3rd figure, which is similar to: The MCP is similar to USB hub in above picture. Due to it being a standard, changes become in a standard way. So less chances of API breaking since each MCP server is now being maintained by individual companies (Yahoo or Google etc.) and we just integrate with them.

An MCP server will expose 3 things:

Tool: Resource: includes knowledge base, DB, files etc. Prompt:

You can refer this for above images.

Setup From Scratch

mkdir mcpserver
npm init
npm install @modelcontextprotocol/sdk

See this for official documentation.

Now in Cursor IDE, click on Settings cog -> MCP. Create the file mcp.json and put below code:

{
    "mcpServers": {
        "Gaurav Kabra's MCP Server": {
        "command": "node",
        "args": ["/Users/gauravkabra/Desktop/MCPServer/index.js"]
        }
    }
}

Replace args with absolute path (full path) of index.js on your local.

And now it should show the add tool available:

You can find documentation here.

Do CMD + I and ask to add two numbers and you should see a response which we coded in index.js.

STDIO (Standard Input-Output) is ideal on local but for remote we use SSE transport (Server Sent Event). See this to know more.

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    Reviews

    1 (1)
    Avatar
    user_CYGCABS7
    2025-04-16

    MCP-Server-AI is an exceptional server tool developed by kabragaurav. Its functionality is impressive, providing seamless AI integration for various applications. The GitHub repository (https://github.com/kabragaurav/MCP-Server) is well-documented, making it easy to implement. Highly recommended for anyone looking to enhance their project with robust AI capabilities!