Custom MCP Server 🤖

A Model Context Protocol (MCP) server built with Next.js, providing useful tools and utilities through both HTTP and Server-Sent Events (SSE) transports.

🚀 Features

🔧 Available Tools

echo - Echo any message back (perfect for testing)
get-current-time - Get the current timestamp and ISO date
calculate - Perform basic mathematical calculations safely

🌐 Transport Methods

HTTP Transport (/mcp) - Stateless HTTP requests (works without Redis)
SSE Transport (/sse) - Server-Sent Events with Redis for state management

🔒 Security Features

Rate limiting (100 requests per minute)
Safe mathematical expression evaluation
Input sanitization and validation

🏃‍♂️ Quick Start

Prerequisites

Node.js 18+
npm or yarn
Docker (optional, for local Redis)

Setup

Clone and install dependencies:
```
npm install
```
Run the automated setup:
```
npm run setup
```
This will:
- Create environment configuration
- Set up Redis (Docker) if available
- Start the development server automatically
Manual start (alternative):
```
npm run dev
```

The server will be available at http://localhost:3000

🧪 Testing

Quick Tests

# Test HTTP transport
npm run test:http

# Test SSE transport (requires Redis)
npm run test:sse

# Test with Claude Desktop protocol
npm run test:stdio

# Comprehensive tool testing
npm run test:tools

Manual Testing

You can test the MCP server manually using curl:

# List available tools
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/list"
  }'

# Call the echo tool
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 2,
    "method": "tools/call",
    "params": {
      "name": "echo",
      "arguments": {
        "message": "Hello World!"
      }
    }
  }'

# Calculate an expression
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 3,
    "method": "tools/call",
    "params": {
      "name": "calculate",
      "arguments": {
        "expression": "15 * 4 + 10"
      }
    }
  }'

🔧 Configuration

Environment Variables

Create a .env.local file:

# Local Redis (Docker)
REDIS_URL=redis://localhost:6379

# Upstash Redis (Production)
UPSTASH_REDIS_REST_URL=your-upstash-url
UPSTASH_REDIS_REST_TOKEN=your-upstash-token

Redis Setup

The server automatically detects and uses Redis in this priority order:

Upstash Redis (if UPSTASH_REDIS_REST_URL and UPSTASH_REDIS_REST_TOKEN are set)
Local Redis (if REDIS_URL is set)
No Redis (HTTP transport only)

Local Redis with Docker

# The setup script handles this automatically, but you can also run manually:
docker run -d --name redis-mcp -p 6379:6379 redis:alpine

Upstash Redis (Recommended for Production)

Create an Upstash Redis database at upstash.com
Add the connection details to your .env.local
The server will automatically detect and use it

🖥️ Integration with AI Tools

Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "custom-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "http://localhost:3000/mcp"
      ]
    }
  }
}

Configuration file locations:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Cursor IDE

For Cursor 0.48.0 or later (direct SSE support):

{
  "mcpServers": {
    "custom-mcp": {
      "url": "http://localhost:3000/sse"
    }
  }
}

For older Cursor versions:

{
  "mcpServers": {
    "custom-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "http://localhost:3000/mcp"
      ]
    }
  }
}

🛠️ Development

Project Structure

custom-mcp-server/
├── app/
│   ├── [transport]/
│   │   └── route.ts          # Main MCP server logic
│   ├── layout.tsx            # Root layout
│   └── page.tsx              # Home page
├── lib/
│   └── redis.ts              # Redis utilities
├── scripts/
│   ├── setup.mjs             # Automated setup
│   ├── test-http-client.mjs  # HTTP transport tests
│   ├── test-sse-client.mjs   # SSE transport tests
│   └── test-tools.mjs        # Comprehensive tool tests
├── package.json
├── next.config.ts
└── README.md

Adding New Tools

Define the tool in app/[transport]/route.ts:

const tools = {
  // ... existing tools
  myNewTool: {
    name: "my-new-tool",
    description: "Description of what your tool does",
    inputSchema: {
      type: "object",
      properties: {
        param1: {
          type: "string",
          description: "Description of parameter"
        }
      },
      required: ["param1"]
    }
  }
};

Add the handler:

const toolHandlers = {
  // ... existing handlers
  "my-new-tool": async ({ param1 }: { param1: string }) => {
    // Your tool logic here
    return {
      content: [
        {
          type: "text",
          text: `Result: ${param1}`
        }
      ]
    };
  }
};

Testing Your Changes

# Run all tests
npm run test:tools

# Test specific functionality
npm run test:http
npm run test:sse

📝 API Reference

Tools/List

Get all available tools:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Tools/Call

Call a specific tool:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "tool-name",
    "arguments": {
      "param": "value"
    }
  }
}

🚀 Deployment

Vercel (Recommended)

Deploy to Vercel:
```
vercel
```
Add environment variables in Vercel dashboard:
- UPSTASH_REDIS_REST_URL
- UPSTASH_REDIS_REST_TOKEN

Update your AI tool configurations to use the deployed URL:

https://your-app.vercel.app/mcp
https://your-app.vercel.app/sse

Other Platforms

The server is a standard Next.js application and can be deployed to any platform that supports Node.js:

Netlify
Railway
Render
DigitalOcean App Platform

🤝 Contributing

Fork the repository
Create a feature branch: git checkout -b feature/my-new-feature
Make your changes and add tests
Run the test suite: npm run test:tools
Commit your changes: git commit -am 'Add some feature'
Push to the branch: git push origin feature/my-new-feature
Submit a pull request

📄 License

MIT License - see LICENSE file for details.

🆘 Troubleshooting

Common Issues

Server not starting:

Check if port 3000 is available
Ensure all dependencies are installed: npm install

Redis connection issues:

Verify Docker is running: docker ps
Check Redis container status: docker ps -a | grep redis-mcp
Restart Redis: docker restart redis-mcp

AI tool not detecting server:

Ensure the server is running and accessible
Check the configuration file syntax (valid JSON)
Restart your AI tool after configuration changes
Verify the server URL is correct

Tool calls failing:

Check server logs for error messages
Test tools manually with npm run test:tools
Verify the tool parameters match the expected schema

Debug Mode

Enable debug logging by setting the environment variable:

DEBUG=1 npm run dev

📞 Support

Create an issue on GitHub for bug reports
Check existing issues for common problems
Review the test scripts for usage examples