MCP Conectar

¿Qué es MCP Connect?

MCP Connect es una herramienta que permite a los servicios de IA basados en la nube acceder a servidores locales del Protocolo de Contexto de Modelo (MCP) basados en Stdio, cerrando la brecha entre los recursos locales y las aplicaciones en la nube.

¿Cómo usar MCP Connect?

Para usar MCP Connect:

• Clona el repositorio
• Configura las variables de entorno
• Instala las dependencias
• Ejecuta la aplicación localmente
• Opcionalmente, ejecútala con un túnel (por ejemplo, Ngrok) para accesibilidad en la nube

Características Clave de MCP Connect

• Integración en la Nube: Conecta herramientas de IA en la nube con servidores MCP locales
• Traducción de Protocolo: Convierte solicitudes HTTP/HTTPS a comunicación Stdio
• Seguridad: Asegura el acceso seguro a recursos locales
• Flexibilidad: Soporta varios servidores MCP sin modificación
• Fácil de Usar: No requiere cambios en el servidor MCP
• Soporte de Túnel: Soporte integrado para túneles Ngrok

Casos de Uso de MCP Connect

• Integrar herramientas de IA locales con aplicaciones basadas en la nube
• Acceder a recursos locales de manera segura desde entornos en la nube
• Facilitar la comunicación entre servicios en la nube y servidores MCP locales

Preguntas Frecuentes sobre MCP Connect

¿Es fácil configurar MCP Connect?

¡Sí! Requiere una configuración mínima y se puede configurar rápidamente.

¿Puedo usar MCP Connect con cualquier servidor MCP?

¡Sí! MCP Connect está diseñado para funcionar con varios servidores MCP sin necesidad de modificaciones.

¿Cuáles son los requisitos previos para usar MCP Connect?

Necesitas tener Node.js instalado para ejecutar MCP Connect.

MCP Connect

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The Model Context Protocol (MCP) introduced by Anthropic is cool. However, most MCP servers are built on Stdio transport, which, while excellent for accessing local resources, limits their use in cloud-based applications.

MCP Connect is a tiny tool that is created to solve this problem:

• Cloud Integration: Enables cloud-based AI services to interact with local Stdio based MCP servers
• Protocol Translation: Converts HTTP/HTTPS requests to Stdio communication
• Security: Provides secure access to local resources while maintaining control
• Flexibility: Supports various MCP servers without modifying their implementation
• Easy to use: Just run MCP Connect locally, zero modification to the MCP server
• Tunnel: Built-in support for Ngrok tunnel

By bridging this gap, we can leverage the full potential of local MCP tools in cloud-based AI applications without compromising on security.

How it works

+-----------------+     HTTPS/SSE      +------------------+      stdio      +------------------+
|                 |                    |                  |                 |                  |
|  Cloud AI tools | <--------------->  |  Node.js Bridge  | <------------>  |    MCP Server    |
|   (Remote)      |       Tunnels      |    (Local)       |                 |     (Local)      |
|                 |                    |                  |                 |                  |
+-----------------+                    +------------------+                 +------------------+

Prerequisites

• Node.js

Quick Start

1. Clone the repository

   git clone https://github.com/EvalsOne/MCP-connect.git
   

   and enter the directory

   cd MCP-connect
   

2. Copy .env.example to .env and configure the port and auth_token:

   cp .env.example .env
   

3. Install dependencies:

   npm install
   

4. Run MCP Connect

   # build MCP Connect
   npm run build
   # run MCP Connect
   npm run start
   # or, run in dev mode (supports hot reloading by nodemon)
   npm run dev
   

Now MCP connect should be running on http://localhost:3000/bridge.

Note:

• The bridge is designed to be run on a local machine, so you still need to build a tunnel to the local MCP server that is accessible from the cloud.
• Ngrok, Cloudflare Zero Trust, and LocalTunnel are recommended for building the tunnel.

Running with Ngrok Tunnel

MCP Connect has built-in support for Ngrok tunnel. To run the bridge with a public URL using Ngrok:

1. Get your Ngrok auth token from https://dashboard.ngrok.com/authtokens
2. Add to your .env file:

   NGROK_AUTH_TOKEN=your_ngrok_auth_token
   

3. Run with tunnel:

   # Production mode with tunnel
   npm run start:tunnel
   
   # Development mode with tunnel
   npm run dev:tunnel
   

After MCP Connect is running, you can see the MCP bridge URL in the console.

API Endpoints

After MCP Connect is running, there are two endpoints exposed:

• GET /health: Health check endpoint
• POST /bridge: Main bridge endpoint for receiving requests from the cloud

For example, the following is a configuration of the official GitHub MCP:

{
  "command": "npx",
  "args": [
    "-y",
    "@modelcontextprotocol/server-github"
  ],
  "env": {
    "GITHUB_PERSONAL_ACCESS_TOKEN": "<your_github_personal_access_token>"
  }
}

You can send a request to the bridge as the following to list the tools of the MCP server and call a specific tool.

Listing tools:

curl -X POST http://localhost:3000/bridge \
     -d '{
       "method": "tools/list",
       "serverPath": "npx",
       "args": [
         "-y",
         "@modelcontextprotocol/server-github"
       ],
       "params": {},
       "env": {
         "GITHUB_PERSONAL_ACCESS_TOKEN": "<your_github_personal_access_token>"
       }
     }'

Calling a tool:

Using the search_repositories tool to search for repositories related to modelcontextprotocol

curl -X POST http://localhost:3000/bridge \
     -d '{
       "method": "tools/call",
       "serverPath": "npx",
       "args": [
         "-y",
         "@modelcontextprotocol/server-github"
       ],
       "params": {
         "name": "search_repositories",
         "arguments": {
            "query": "modelcontextprotocol"
         },
       },
       "env": {
         "GITHUB_PERSONAL_ACCESS_TOKEN": "<your_github_personal_access_token>"
       }
     }'

Authentication

MCP Connect uses a simple token-based authentication system. The token is stored in the .env file. If the token is set, MCP Connect will use it to authenticate the request.

Sample request with token:

curl -X POST http://localhost:3000/bridge \
     -H "Authorization: Bearer <your_auth_token>" \
     -d '{
       "method": "tools/list",
       "serverPath": "npx",
       "args": [
         "-y",
         "@modelcontextprotocol/server-github"
       ],
       "params": {},
       "env": {
         "GITHUB_PERSONAL_ACCESS_TOKEN": "<your_github_personal_access_token>"
       }
     }'

Configuration

Required environment variables:

• AUTH_TOKEN: Authentication token for the bridge API (Optional)
• PORT: HTTP server port (default: 3000, required)
• LOG_LEVEL: Logging level (default: info, required)
• NGROK_AUTH_TOKEN: Ngrok auth token (Optional)

Using MCP Connect with ConsoleX AI to access local MCP Server

The following is a demo of using MCP Connect to access a local MCP Server on ConsoleX AI:

License

MIT License