NetADX AI-CORE MCP API Boilerplate

NetADX AI-CORE MCP API Boilerplate

A minimal, production-ready MCP server boilerplate for building AI-powered backend services with TypeScript, MongoDB, and JWT authentication.

Category
Visit Server

README

NetADX AI-CORE - MCP API Boilerplate

TypeScript License: MIT MCP SDK Node.js NetADX AI-CORE OpenAPI Swagger UI

A minimal, production-ready MCP (Model Context Protocol) API server boilerplate for building scalable AI-powered backend services.

Purpose: Simple, extensible foundation for building MCP-compliant API servers with TypeScript, MongoDB, and JWT authentication.

Architecture: Clean, minimal structure - easy to understand and extend for your specific use case.

Table of Contents

Overview

NetADX AI-CORE is a simple, clean boilerplate for building MCP API servers. It provides:

  • MCP Protocol Compliance - Official SDK v1.0.0
  • TypeScript - Type-safe development
  • MongoDB Integration - Database ready with connection pooling
  • JWT Authentication - Secure API access
  • Interactive API Documentation - Comprehensive Swagger/OpenAPI 3.0 docs
  • Direct TypeScript Execution - No build step with tsx
  • Production Ready - Logging, error handling, graceful shutdown
  • Minimal and Clean - Easy to understand and extend

What's Included

Core Infrastructure:

  • MCP Server setup with stdio and HTTP transports
  • MongoDB connection manager
  • JWT authentication manager
  • Winston logging
  • Environment configuration
  • Example CRUD tool
  • Interactive Swagger documentation at /docs

Deployment:

  • Quick deployment script (deploy-quick.sh)
  • PM2 ecosystem configuration
  • Docker support
  • Nginx reverse proxy with CORS
  • Comprehensive deployment documentation

Claude Desktop Integration:

  • Built-in stdio wrapper support
  • Local development with development/mcp-stdio-wrapper
  • Production-ready npm package @netadx1ai/mcp-stdio-wrapper
  • Complete integration documentation

Features

Direct TypeScript Execution

No build step required! Uses tsx to run TypeScript directly:

# Traditional approach (NOT used here)
npm run build        # Compile TS → JS
node dist/index.js   # Run compiled code

# NetADX AI-CORE approach
npx tsx src/index.ts  # Run TypeScript directly

Benefits:

  • Faster deployments - no compilation step required
  • Easier debugging - errors point to actual .ts source files
  • Live updates - change code, restart, ready
  • Simpler CI/CD - just sync TypeScript files directly

Technology Stack

  • Runtime: Node.js 18+
  • Language: TypeScript 5.2+ (strict mode)
  • Framework: MCP Protocol (official SDK v1.0.0)
  • Database: MongoDB with connection pooling
  • Transport: HTTP/HTTPS + stdio
  • Authentication: JWT (HS256)
  • Logging: Winston
  • Execution: tsx (direct TypeScript execution)

Quick Start

Prerequisites

# Node.js 18+ required
node -v

# MongoDB (local or remote)
mongod --version

Installation

# Clone or use this boilerplate
cd development/mcp_aicore_boilerplate

# Install dependencies
npm install

# Configure environment
cp .env.example .env
nano .env  # Edit with your settings

Configuration

Edit .env file:

# Server
NODE_ENV=development
PORT=8005
USE_HTTP=true

# MongoDB
MONGODB_URI=mongodb://localhost:27017/netadx_aicore

# JWT
JWT_SECRET=your-secure-random-secret-here
JWT_EXPIRES_IN=24h

# Logging
LOG_LEVEL=info

Run

# Development mode
npm run dev

# Production mode (with tsx)
npm start

# Or directly
npx tsx src/index.ts

Test

# Health check
curl http://localhost:8005/health

# List tools (requires JWT token)
curl -H "x-access-token: YOUR_JWT_TOKEN" \
     http://localhost:8005/tools

# Call example tool
curl -X POST \
  -H "x-access-token: YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action":"list_items"}' \
  http://localhost:8005/tools/example_tool

Interactive API Documentation

Swagger/OpenAPI 3.0 Documentation

The boilerplate includes comprehensive interactive API documentation powered by Swagger UI and OpenAPI 3.0 specification.

Access Documentation:

# Start the server
npm run dev

# Open documentation in browser
open http://localhost:8005/docs

Features:

  • šŸš€ Interactive Testing - Test all endpoints directly from the browser
  • šŸ” Built-in Authentication - JWT and API key authentication flows
  • šŸ“ Comprehensive Examples - Real request/response examples for every endpoint
  • āœ… Schema Validation - Request/response validation against OpenAPI schemas
  • šŸ“Š Error Documentation - Complete error codes and recovery suggestions
  • ⚔ Performance Metrics - Response time tracking and optimization tips

Key Endpoints Documented:

  • GET /health - System health check with performance metrics
  • GET /info - Server information and capabilities
  • GET /tools - List all available MCP tools
  • POST /tools/{name} - Execute specific MCP tools with validation
  • POST /rpc - JSON-RPC 2.0 endpoint for MCP communication

Authentication Methods:

  • JWT Bearer Token: Authorization: Bearer <token>
  • API Key: X-API-Key: <key>

Quick Test Example:

# Test health endpoint (no auth required)
curl http://localhost:8005/health

# List tools (requires auth)
curl -H "Authorization: Bearer your-jwt-token" \
     http://localhost:8005/tools

# Execute example tool
curl -X POST \
  -H "Authorization: Bearer your-jwt-token" \
  -H "Content-Type: application/json" \
  -d '{"arguments": {"action": "list_items"}}' \
  http://localhost:8005/tools/example-tool

For detailed documentation about the Swagger implementation, see: MCP AI-Core Swagger Documentation

Project Structure

mcp_aicore_boilerplate/
ā”œā”€ā”€ src/
│   ā”œā”€ā”€ index.ts                 # Main entry point
│   ā”œā”€ā”€ core/                    # MCP core infrastructure
│   │   ā”œā”€ā”€ server.ts           # Base MCP server
│   │   └── index.ts
│   ā”œā”€ā”€ tools/                   # MCP tools (your business logic)
│   │   └── example-tool.ts     # Example CRUD tool
│   ā”œā”€ā”€ swagger/                 # API documentation
│   │   ā”œā”€ā”€ index.ts            # Main Swagger/OpenAPI configuration
│   │   ā”œā”€ā”€ tools.ts            # Tool-specific documentation
│   │   └── endpoints.ts        # Endpoint documentation
│   ā”œā”€ā”€ transport/               # Transport layers
│   │   ā”œā”€ā”€ http.ts             # HTTP transport with Swagger integration
│   │   ā”œā”€ā”€ http-server.ts      # HTTP server wrapper
│   │   └── index.ts
│   ā”œā”€ā”€ utils/                   # Utilities
│   │   ā”œā”€ā”€ auth.ts             # JWT authentication
│   │   ā”œā”€ā”€ config.ts           # Configuration management
│   │   ā”œā”€ā”€ logger.ts           # Winston logging
│   │   ā”œā”€ā”€ mongodb.ts          # MongoDB manager
│   │   └── index.ts
│   └── types/                   # TypeScript type definitions
│       └── index.ts
ā”œā”€ā”€ deployment/                  # Deployment configurations
│   ā”œā”€ā”€ deploy.sh               # Full deployment script
│   ā”œā”€ā”€ pm2/                    # PM2 configs
│   ā”œā”€ā”€ docker/                 # Docker configs
│   ā”œā”€ā”€ nginx/                  # Nginx reverse proxy with CORS
│   └── README.md
ā”œā”€ā”€ docs/                        # Documentation (cleaned)
ā”œā”€ā”€ .env.example                 # Environment template (simplified)
ā”œā”€ā”€ .env.deploy.example          # Deployment config template
ā”œā”€ā”€ deploy-quick.sh              # Quick TypeScript deployment
ā”œā”€ā”€ ecosystem.config.js          # PM2 config (uses tsx)
ā”œā”€ā”€ package.json                 # Dependencies
ā”œā”€ā”€ tsconfig.json                # TypeScript config
└── README.md                    # This file

Configuration

Environment Variables

All configuration in .env file:

# Server Configuration
NODE_ENV=development          # development | staging | production
PORT=8005                     # API server port
HOST=0.0.0.0                  # Listen address
USE_HTTP=true                 # true = HTTP, false = stdio

# MongoDB
MONGODB_URI=mongodb://localhost:27017/netadx_aicore
MONGODB_MAX_POOL_SIZE=50

# JWT Authentication
JWT_SECRET=change-this-secret
JWT_EXPIRES_IN=24h
JWT_ALGORITHM=HS256

# CORS
CORS_ORIGIN=http://localhost:3000
CORS_CREDENTIALS=true

# Logging
LOG_LEVEL=info               # error | warn | info | debug
LOG_FORMAT=json
LOG_FILE=/var/log/netadx-aicore/app.log

MongoDB Collections

The example tool uses example_items collection. Add your own collections as needed.

Development

Adding a New Tool

  1. Create tool file in src/tools/:
// src/tools/my-tool.ts
import { z } from 'zod';
import type { MongoDBManager } from '../utils/mongodb';
import type { Logger } from '../utils/logger';

const MyToolInputSchema = z.object({
  action: z.enum(['do_something']),
  data: z.string(),
});

export function createMyTool(mongodb: MongoDBManager, logger: Logger) {
  return {
    name: 'my_tool',
    description: 'My custom tool',
    inputSchema: {
      type: 'object',
      properties: {
        action: { type: 'string', enum: ['do_something'] },
        data: { type: 'string' },
      },
      required: ['action'],
    },
    async execute(input: unknown) {
      const { action, data } = MyToolInputSchema.parse(input);
      
      // Your logic here
      const result = { success: true, message: 'Done!' };
      
      return {
        content: [{ type: 'text', text: JSON.stringify(result, null, 2) }],
      };
    },
  };
}
  1. Register tool in src/index.ts:
import { createMyTool } from './tools/my-tool';

// In registerTools() method:
const myTool = createMyTool(this.mongodb, this.logger);

// Add to tools list
this.server.setRequestHandler('tools/list', async () => {
  return {
    tools: [
      { name: exampleTool.name, description: exampleTool.description, inputSchema: exampleTool.inputSchema },
      { name: myTool.name, description: myTool.description, inputSchema: myTool.inputSchema },
    ],
  };
});

// Add to tools/call handler
if (name === myTool.name) {
  return await myTool.execute(args);
}
  1. Test your tool:
npx tsx src/index.ts

curl -X POST \
  -H "x-access-token: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action":"do_something","data":"test"}' \
  http://localhost:8005/tools/my_tool

Running Tests

# Add tests in tests/ directory
npm test

Code Quality

# Linting
npm run lint

# Format code
npm run format

# Type checking
npm run type-check

Deployment

Quick Deployment (Recommended)

Uses deploy-quick.sh to sync TypeScript files directly:

# Configure deployment
cp .env.deploy.example .env.deploy
nano .env.deploy  # Set your server details

# Deploy all files
./deploy-quick.sh

# Deploy specific file
./deploy-quick.sh src/tools/my-tool.ts

# Deploy without restart
./deploy-quick.sh src/ true

PM2 Deployment

# Start with PM2
pm2 start ecosystem.config.js --env production

# Monitor
pm2 status
pm2 logs netadx-aicore
pm2 monit

Docker Deployment

cd deployment/docker
docker build -t netadx-aicore .
docker run -d -p 8005:8005 --env-file .env netadx-aicore

Nginx Reverse Proxy

# Copy nginx config
sudo cp deployment/nginx/netadx-aicore-simple.conf /etc/nginx/sites-available/netadx-aicore

# Enable and reload
sudo ln -s /etc/nginx/sites-available/netadx-aicore /etc/nginx/sites-enabled/
sudo nginx -t
sudo systemctl reload nginx

See deployment/README.md and deployment/nginx/README.md for complete guides.

Claude Desktop Integration

Using Published Package (Production)

Configure Claude Desktop to connect to your deployed API:

File: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)

{
  "mcpServers": {
    "netadx-aicore": {
      "command": "npx",
      "args": ["-y", "@netadx1ai/mcp-stdio-wrapper@latest"],
      "env": {
        "API_URL": "https://your-api-domain.com",
        "JWT_TOKEN": "your-jwt-token-here",
        "LOG_FILE": "/tmp/netadx-aicore-mcp.log",
        "LOG_LEVEL": "info"
      }
    }
  }
}

Using Local Development Wrapper

For local development and testing:

{
  "mcpServers": {
    "netadx-aicore-dev": {
      "command": "npx",
      "args": [
        "tsx",
        "/Volumes/T72/Work2025AI/mongodb/netadx-workspace/development/mcp-stdio-wrapper/src/index.ts"
      ],
      "env": {
        "API_URL": "http://localhost:8005",
        "JWT_TOKEN": "your-jwt-token-here",
        "LOG_FILE": "/tmp/netadx-aicore-dev-mcp.log",
        "LOG_LEVEL": "debug"
      }
    }
  }
}

See Claude Desktop Integration Guide for complete documentation.

API Documentation

Authentication

All API endpoints (except /health) require JWT authentication:

# Include JWT token in header
curl -H "x-access-token: YOUR_JWT_TOKEN" http://localhost:8005/tools

Endpoints

Endpoint Method Description Documentation
/health GET Health check (no auth) Interactive Docs
/info GET Server information (no auth) Interactive Docs
/tools GET List available tools Interactive Docs
/tools/{tool_name} POST Execute specific tool Interactive Docs
/rpc POST JSON-RPC 2.0 endpoint Interactive Docs
/docs GET Swagger documentation Direct browser access

Example Tool Actions

List items:

curl -X POST \
  -H "x-access-token: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action":"list_items"}' \
  http://localhost:8005/tools/example_tool

Create item:

curl -X POST \
  -H "x-access-token: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action":"create_item","data":{"name":"Test","value":123}}' \
  http://localhost:8005/tools/example_tool

Get item:

curl -X POST \
  -H "x-access-token: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action":"get_data","id":"item_id"}' \
  http://localhost:8005/tools/example_tool

Contributing

This is a boilerplate template. Fork it and customize for your needs!

License

MIT License - NetADX AI-CORE Team


Learning Resources

Support

For questions or issues:

  • Check the deployment/README.md for deployment help
  • Check the deployment/nginx/README.md for nginx/CORS help
  • Review the example tool in src/tools/example-tool.ts
  • See Claude Desktop Integration for MCP client setup

Document Control

  • Created: 2025-10-31
  • Version: 1.0.0
  • Status: Boilerplate/Template
  • Developed by: NetADX AI-CORE Team
  • License: MIT

What is NetADX AI-CORE?

NetADX AI-CORE is a production-ready boilerplate for building MCP (Model Context Protocol) compliant API servers. It provides:

  • Complete MCP implementation with official SDK v1.0.0
  • Production-tested authentication and authorization
  • Scalable MongoDB integration
  • Comprehensive logging and error handling
  • Direct TypeScript execution (no build step)
  • Deployment scripts and configurations
  • Clean, minimal, easy to extend
  • Claude Desktop integration support

Use Cases:

  • Building AI-powered backend APIs
  • Creating MCP-compliant services
  • Rapid API prototyping
  • Learning MCP protocol implementation

Get Started:

  1. Copy .env.example to .env
  2. Configure MongoDB and JWT settings
  3. Run npm install && npm start
  4. Start building your tools in src/tools/
  5. Integrate with Claude Desktop using the stdio wrapper

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured