Alesion30 My MCP Server

🚀 My MCP Server

This project provides a custom MCP server, which is a standardized protocol enabling applications to provide context to Large Language Models (LLMs). It serves as the USB - C port for AI applications, allowing AI models to connect to various data sources and tools through a standard approach.

🚀 Quick Start

Step 1: Download Claude Desktop

Get Claude Desktop from here.

Step 2: Build a Custom MCP Server

Execute the following commands in the terminal:

$ npm install
$ npm run build

# Display the full path of build/main.js
$ find `pwd` -maxdepth 2 -name main.js

Step 3: Register the MCP Server in Claude Desktop Settings

⚠️ Important Note The following steps are for the macOS version. For other operating systems, refer to the official documentation.

$ vi ~/Library/Application\ Support/Claude/claude_desktop_config.json

Step 4: Configure the Server

Add the following content to the configuration file:

{
  "mcpServers": [
    {
      "name": "customMCP",
      "url": "http://localhost:1234"
    }
  ]
}

Step 5: Register in Claude Desktop

Launch Claude Desktop, access the settings menu, select "Manage MCP Servers", and click the "Add" button. Enter the following information:

• Name: customMCP
• Type: HTTP
• Address: http://localhost:1234 Save the settings and restart Claude Desktop.

Step 6: Verify the Configuration

Run the following command in the terminal to verify if the server is correctly registered:

$ curl http://localhost:1234/ping

A successful response indicates that the configuration is complete.

✨ Features

MCP (Model Context Protocol)

MCP is a standardized protocol for applications to provide context to LLMs. It's like the USB - C port for AI applications, enabling AI models to connect to various data sources and tools via a standard method.

flowchart LR
  User(fa:fa-user User)
  Client["""
  Host with MCP Client
  (Claude, IDE, Tools)
  """]

  Server1["MCP Server A"]
  Server2["MCP Server B"]
  Server3["MCP Server C"]

  DB1[Local Data Source A]
  DB2[Local Data Source B]
  Services[Remote Services]

  subgraph Local Computer
  User <--> Client
  Client <--> |MCP Protocol| Server1
  Client <--> |MCP Protocol| Server2
  Client <--> |MCP Protocol| Server3

  Server1 <--> DB1
  Server2 <--> DB2
  end

  subgraph Internet
  Server2 <--> |Web API| Services
  Server3 <--> |Web API| Services
  end

Reference: https://modelcontextprotocol.io/introduction

Similar Concept: Function Calling

flowchart LR
  User(fa:fa-user User)
  Server[Application Server]
  OpenAI[OpenAI API]

  Function1[Function A on Server]
  Function2[Function B on Server]
  Function3[Function C on Server]
  DB[Local Data Source]
  Services[Remote Services]

  subgraph Local Computer
  User <--> Server
  Server <--> Function1
  Server <--> Function2
  Server <--> Function3
  Function1 <--> DB
  Function2 <--> DB
  end

  subgraph "Internet (OpenAI)"
  Server --> |Prompt| OpenAI
  OpenAI --> |Response with Function Call| Server
  end

  subgraph Internet
  Function2 <--> |Web APIs| Services
  Function3 <--> |Web APIs| Services
  end

Reference: https://platform.openai.com/docs/guides/function-calling

📚 Documentation

Image References

MCP Server Structure

Function Calling Example