MCP Tool AI

This repository contains a configurable Model Context Protocol (MCP) gateway. It runs multiple Streamable HTTP MCP servers and exposes all of their tools through one gateway endpoint that can be used from Cursor, Antigravity, or any other MCP client that supports Streamable HTTP.

Project Structure

• mcp1.ts - MCP Server 1 on port 3000
  • add_number
  • subtract_number
• mcp2.ts - MCP Server 2 on port 3001
  • multiply_number
  • divide_number
• mcp-ai.ts - AI API MCP server on port 3002
  • list_ai_providers
  • list_ai_models
  • chat_with_model
  • openai_compatible_request
• mcp-gateway.ts - Gateway server on port 8000
  • Lists tools from both backend servers.
  • Prefixes tool names with the backend id, such as 1/add_number or ai/chat_with_model.
  • Routes tool calls back to the correct MCP server.
• config.ts - Shared environment configuration.
• .env.example - Example environment configuration.

Requirements

• Node.js 20 or newer
• npm

Install

npm install

Create a .env file from .env.example and add your provider keys:

PowerShell:

Copy-Item .env.example .env

Bash:

cp .env.example .env

For NVIDIA hosted NIM, set:

AI_PROVIDERS=nvidia
AI_DEFAULT_PROVIDER=nvidia
AI_NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1
AI_NVIDIA_MODEL=openai/gpt-oss-120b
AI_NVIDIA_API_KEY=your-key-here

NVIDIA NIM exposes OpenAI-compatible endpoints such as POST /v1/chat/completions and GET /v1/models.

Run

Run everything in one terminal:

npm run all

Or open four terminals from the project folder.

Terminal 1:

npm run server1

Terminal 2:

npm run server2

Terminal 3:

npm run ai

Terminal 4:

npm run gateway

Endpoints:

• Server 1: http://localhost:3000/mcp
• Server 2: http://localhost:3001/mcp
• AI Server: http://localhost:3002/mcp
• Gateway: http://localhost:8000/mcp

Use the gateway URL in MCP clients:

http://localhost:8000/mcp

Type Check

npm run typecheck

Notes

The gateway uses Streamable HTTP clients to connect to the backend MCP servers. When a client lists tools from the gateway, the gateway fetches tools from each registered backend and returns unique names in the format:

<server-id>/<tool-name>

For example:

• 1/add_number
• 1/subtract_number
• 2/multiply_number
• 2/divide_number
• ai/list_ai_providers
• ai/list_ai_models
• ai/chat_with_model
• ai/openai_compatible_request

Environment Configuration

All ports, paths, gateway entries, and AI providers are controlled by env vars.

Core MCP settings:

MCP_LISTEN_HOST=127.0.0.1
MCP_PUBLIC_HOST=localhost
MCP_PATH=/mcp
MCP1_PORT=3000
MCP2_PORT=3001
MCP_AI_PORT=3002
MCP_GATEWAY_PORT=8000
MCP_GATEWAY_SERVERS=1,2,ai

AI provider settings:

AI_PROVIDERS=nvidia,my-local-api
AI_DEFAULT_PROVIDER=nvidia

AI_NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1
AI_NVIDIA_MODEL=openai/gpt-oss-120b
AI_NVIDIA_API_KEY=your-key-here

AI_MY_LOCAL_API_BASE_URL=http://localhost:11434/v1
AI_MY_LOCAL_API_MODEL=llama3.1
AI_MY_LOCAL_API_API_KEY=

Every provider is assumed to be OpenAI-compatible. The AI MCP server adds the configured key as an Authorization: Bearer ... header by default.