MCP Conectar

O que é o MCP Connect?

MCP Connect é uma ferramenta que permite que serviços de IA baseados em nuvem acessem servidores locais do Protocolo de Contexto de Modelo (MCP) baseados em Stdio, conectando recursos locais a aplicativos em nuvem.

Como usar o MCP Connect?

Para usar o MCP Connect:

• Clone o repositório
• Configure as variáveis de ambiente
• Instale as dependências
• Execute o aplicativo localmente
• Opcionalmente, execute-o com um túnel (por exemplo, Ngrok) para acessibilidade na nuvem

Principais Recursos do MCP Connect

• Integração com a Nuvem: Conecta ferramentas de IA em nuvem com servidores MCP locais
• Tradução de Protocolo: Converte solicitações HTTP/HTTPS em comunicação Stdio
• Segurança: Garante acesso seguro a recursos locais
• Flexibilidade: Suporta vários servidores MCP sem modificação
• Fácil de Usar: Não requer alterações no servidor MCP
• Suporte a Túnel: Suporte embutido para túnel Ngrok

Casos de Uso do MCP Connect

• Integrar ferramentas de IA locais com aplicativos baseados em nuvem
• Acessar recursos locais de forma segura a partir de ambientes em nuvem
• Facilitar a comunicação entre serviços em nuvem e servidores MCP locais

Perguntas Frequentes sobre o MCP Connect

O MCP Connect é fácil de configurar?

Sim! Requer configuração mínima e pode ser configurado rapidamente.

Posso usar o MCP Connect com qualquer servidor MCP?

Sim! O MCP Connect foi projetado para funcionar com vários servidores MCP sem necessidade de modificações.

Quais são os pré-requisitos para usar o MCP Connect?

Você precisa ter o Node.js instalado para executar o 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