Industrial MCP

❌ Traditional Approach:
   AI Model ←→ Custom API 1 ←→ Machine 1 (Modbus)
   AI Model ←→ Custom API 2 ←→ Machine 2 (OPC UA)  
   AI Model ←→ Custom API 3 ←→ Machine 3 (MQTT)
   = N×M integration nightmare 😱

✅ With Industrial MCP:
   AI Model ←→ MCP Protocol ←→ Industrial MCP Server ←→ Any Machine
   = One standard interface for everything 🎉

# Clone the repository
git clone https://github.com/YOUR_USERNAME/industrial-mcp.git
cd industrial-mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -e .

from industrial_mcp import MCPServer, ModbusAdapter

# Create MCP server
server = MCPServer(name="my-factory")

# Connect to a Modbus device (e.g., a pump)
pump = ModbusAdapter(
    host="192.168.1.100",
    port=502,
    device_name="pump-01"
)

# Register the device
server.register_device(pump)

# Define tools that AI can use
@server.tool("get_pump_status")
async def get_pump_status():
    """Get the current status of the main pump"""
    temp = await pump.read_register(address=100)
    vibration = await pump.read_register(address=101)
    return {
        "temperature": temp,
        "vibration": vibration,
        "status": "normal" if vibration < 50 else "warning"
    }

# Start the MCP server
server.run(host="0.0.0.0", port=8080)

{
  "mcpServers": {
    "industrial": {
      "command": "python",
      "args": ["-m", "industrial_mcp", "--config", "config.yaml"]
    }
  }
}

┌─────────────────────────────────────────────────────────────┐
│                     YOUR FACTORY                            │
│                                                             │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────┐     │
│  │ Machine 1│  │ Machine 2│  │ Machine 3│  │ Sensor N │     │
│  │ (Modbus) │  │ (OPC UA) │  │  (MQTT)  │  │ (Modbus) │     │
│  └────┬─────┘  └────┬─────┘  └────┬─────┘  └────┬─────┘     │
│       │             │             │             │           │
│       └─────────────┴──────┬──────┴─────────────┘           │
│                            │                                │
│                   ┌────────▼────────┐                       │
│                   │  INDUSTRIAL MCP │                       │
│                   │     SERVER      │  ← Runs on Edge       │
│                   │  ┌────────────┐ │                       │
│                   │  │  Adapters  │ │                       │
│                   │  │  ┌──────┐  │ │                       │
│                   │  │  │Modbus│  │ │                       │
│                   │  │  │OPC UA│  │ │                       │
│                   │  │  │ MQTT │  │ │                       │
│                   │  │  └──────┘  │ │                       │
│                   │  └────────────┘ │                       │
│                   │  ┌────────────┐ │                       │
│                   │  │ MCP Server │ │                       │
│                   │  └────────────┘ │                       │
│                   └────────┬────────┘                       │
│                            │                                │
└────────────────────────────┼────────────────────────────────┘
                             │ MCP Protocol (JSON-RPC)
                             ▼
                   ┌─────────────────┐
                   │    AI CLIENT    │
                   │  Claude / GPT   │
                   │  Local LLM      │
                   └─────────────────┘

@server.tool("analyze_vibration_pattern")
async def analyze_vibration():
    """Compare current vibration with historical failure patterns"""
    current = await pump.read_vibration()
    historical = await db.get_failure_patterns()
    similarity = calculate_similarity(current, historical)
    return {
        "similarity_to_failure": f"{similarity}%",
        "recommendation": "Schedule inspection" if similarity > 80 else "Normal"
    }

@server.tool("get_production_status")
async def get_production():
    """Get real-time production line status"""
    return {
        "units_produced": await plc.read("production_count"),
        "efficiency": await calculate_oee(),
        "downtime_minutes": await get_downtime()
    }

@server.tool("check_anomalies")
async def check_anomalies():
    """Detect anomalies across all connected devices"""
    anomalies = []
    for device in server.devices:
        if await device.is_anomalous():
            anomalies.append(device.name)
    return {"anomalies": anomalies, "count": len(anomalies)}

# Install on Raspberry Pi
curl -sSL https://get.industrial-mcp.io | bash

# Or manually
pip install industrial-mcp[raspberry]

# Optimized for Jetson with local LLM support
pip install industrial-mcp[jetson]

docker run -d \
  --name industrial-mcp \
  -p 8080:8080 \
  -v ./config.yaml:/app/config.yaml \
  industrialmcp/server:latest

# Clone and install dev dependencies
git clone https://github.com/YOUR_USERNAME/industrial-mcp.git
cd industrial-mcp
pip install -e ".[dev]"

# Run tests
pytest

# Run linting
ruff check .