intecrel/industrial-mcp
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A comprehensive Model Context Protocol (MCP) server designed for industrial system monitoring and control.
🏭 Industrial MCP Server
A comprehensive Model Context Protocol (MCP) server designed for industrial system monitoring and control. Built with Next.js, TypeScript, and the Vercel MCP adapter, this server provides Claude AI with powerful tools to interact with industrial systems.
🚀 Live Demo
- Production Server: https://industrial-mcp-delta.vercel.app
- MCP Endpoint: https://industrial-mcp-delta.vercel.app/api/mcp
- Health Check: https://industrial-mcp-delta.vercel.app/api/health
✨ Features
Available MCP Tools
- 🔄 Echo Tool - Basic communication testing
- 📊 System Status - Real-time industrial system health monitoring
- 📈 Operational Data - Performance metrics and analytics
- 🔧 Equipment Monitor - Individual equipment status and maintenance tracking
Industrial Metrics Provided
- System uptime and health status
- CPU, memory, disk, and network monitoring
- Throughput and performance analytics
- Equipment temperature, vibration, and pressure readings
- Maintenance scheduling and alerts
- Historical trend analysis
🛠️ Quick Start
Prerequisites
- Node.js 18+
- npm or yarn
- Git
Installation
- Clone the repository:
git clone https://github.com/intecrel/industrial-mcp.git
cd industrial-mcp
- Install dependencies:
npm install
- Start development server:
npm run dev
- Verify the server is running:
# Test basic endpoint
curl http://localhost:3000/api/mcp
# Test MCP protocol initialization
curl -X POST http://localhost:3000/api/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {"roots": {"listChanged": false}},
"clientInfo": {"name": "test-client", "version": "1.0.0"}
}
}'
🧪 Testing with MCP Inspector
The MCP Inspector provides a web interface for testing your MCP server:
# Install MCP Inspector globally
npm install -g @modelcontextprotocol/inspector
# Run inspector against local server
mcp-inspector http://localhost:3000/api/mcp
# Or run against production server
mcp-inspector https://industrial-fvucjqopi-samuels-projects-2dd2e35e.vercel.app/api/mcp
🤖 Claude Desktop Integration
To connect this MCP server to Claude Desktop:
1. Edit Claude Desktop Configuration
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
2. Add Server Configuration
{
"mcpServers": {
"industrial-mcp": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-fetch",
"http://localhost:3000/api/mcp"
]
}
}
}
3. Restart Claude Desktop
After saving the configuration, restart Claude Desktop to load the new MCP server.
4. Test in Claude
You can now use commands like:
- "Get the industrial system status"
- "Show me operational data for the last 24 hours"
- "Monitor equipment ID-12345 with history"
- "Echo test message"
🌐 Deployment
Deploy to Vercel
# Install Vercel CLI
npm install -g vercel
# Deploy to Vercel
vercel
# Deploy to production
vercel --prod
📁 Project Structure
industrial-mcp/
├── app/
│ ├── api/
│ │ └── [transport]/
│ │ └── route.ts # Main MCP server implementation
│ ├── dashboard/
│ │ └── page.tsx # Web dashboard
│ ├── globals.css # Global styles
│ ├── layout.tsx # Root layout
│ └── page.tsx # Home page
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── tailwind.config.js # Tailwind CSS configuration
├── next.config.js # Next.js configuration
└── README.md # This file
🔧 API Reference
MCP Protocol Endpoints
All MCP communication happens via JSON-RPC 2.0 over HTTP:
Base URL: /api/mcp
Initialize Connection
{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {"roots": {"listChanged": false}},
"clientInfo": {"name": "client", "version": "1.0.0"}
}
}
List Available Tools
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/list",
"params": {}
}
Call a Tool
{
"jsonrpc": "2.0",
"id": 3,
"method": "tools/call",
"params": {
"name": "get_system_status",
"arguments": {}
}
}
Tool Specifications
Echo Tool
- Name:
echo - Parameters:
message(string, required) - Returns: Echoed message
System Status Tool
- Name:
get_system_status - Parameters: None
- Returns: System health metrics, uptime, alerts
Operational Data Tool
- Name:
get_operational_data - Parameters:
timeRange(string, optional): "1h", "24h", "7d"system(string, optional): Specific system to query
- Returns: Performance metrics and trends
Equipment Monitor Tool
- Name:
monitor_equipment - Parameters:
equipmentId(string, required): Equipment identifierincludeHistory(boolean, optional): Include historical data
- Returns: Equipment status, metrics, maintenance info
🐛 Troubleshooting
Common Issues
-
"Cannot find module '@vercel/mcp-adapter'"
npm install @vercel/mcp-adapter -
"Method not allowed" errors
- Ensure you're using POST requests for MCP protocol
- Include proper headers:
Content-Type: application/jsonandAccept: application/json, text/event-stream
-
Connection refused in Claude Desktop
- Verify the server is running on the correct port
- Check Claude Desktop configuration file syntax
- Restart Claude Desktop after configuration changes
-
Build errors on deployment
npm run build # Test build locally first npm run lint # Fix any linting issues
Debug Mode
Enable verbose logging by setting the environment variable:
DEBUG=mcp:* npm run dev
🤝 Contributing
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Commit changes:
git commit -m 'Add amazing feature' - Push to branch:
git push origin feature/amazing-feature - Open a Pull Request
📄 License
This project is licensed under the MIT License - see the file for details.
🙏 Acknowledgments
- Model Context Protocol - The protocol specification
- Vercel MCP Adapter - MCP implementation for Vercel
- Claude AI - AI assistant integration
- Next.js - React framework
- Anthropic - MCP protocol development
📞 Support
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Email: sam@industrial.marketing
Made with ❤️ for Industrial Automation and AI Integration