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EdgeAI MCP

Industrial MCP is an open-source project that implements the Model Context Protocol (MCP) for industrial environments. It allows any AI model (Claude, GPT, Mistral, Llama, etc.) to read data from and control industrial equipment through a standardized interface.

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About EdgeAI MCP

EdgeAI MCP is an MCP server in the IoT category: industrial MCP is an open-source project that implements the Model Context Protocol (MCP) for industrial environments. It allows any AI model (Claude, GPT, Mistral, Llama, etc.) to read data from and control industrial equipment through a standardized interface. It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/xiao98/EdgeAI-MCP

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README


🌟 What is Industrial MCP?

Industrial MCP is an open-source project that implements the Model Context Protocol (MCP) for industrial environments. It allows any AI model (Claude, GPT, Mistral, Llama, etc.) to read data from and control industrial equipment through a standardized interface.

Think of it as USB-C for Industrial AI — one universal connector for all your machines.

The Problem We Solve

❌ 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 🎉

✨ Features

Feature Description
🔌 Multi-Protocol Support Modbus TCP/RTU, OPC UA, MQTT, S7 (Siemens)
🤖 AI-Ready Works with Claude, ChatGPT, Mistral, local LLMs
📍 Edge-First Runs on Raspberry Pi, Jetson, any Linux device
🔒 Data Sovereignty All processing on-premise, no cloud required
🇪🇺 GDPR Compliant Data never leaves your factory
💬 Natural Language Talk to your machines in plain language
📊 Built-in Monitoring Real-time dashboards and alerts
🔧 Extensible Add custom protocols with simple Python plugins

🚀 Quick Start

Installation

# 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 .

Basic Usage

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)

Connect with Claude Desktop

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

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

Now you can ask Claude:

"What's the temperature of pump-01?"
"Is the vibration level normal?"
"Show me the status of all connected devices."


📡 Supported Protocols

Protocol Status Use Case
Modbus TCP ✅ Stable PLCs, sensors, meters
Modbus RTU ✅ Stable Serial devices, RS-485
OPC UA ✅ Stable Modern industrial systems
MQTT ✅ Stable IoT sensors, lightweight devices
Siemens S7 🔄 Beta Siemens PLCs (S7-300/400/1200/1500)
BACnet 📋 Planned Building automation
EtherNet/IP 📋 Planned Allen-Bradley, Rockwell

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                     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      │
                   └─────────────────┘

💡 Use Cases

🔧 Predictive Maintenance

@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"
    }

📊 Real-time Monitoring

@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()
    }

🚨 Anomaly Detection

@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)}

🖥️ Edge Deployment

Raspberry Pi 4/5

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

# Or manually
pip install industrial-mcp[raspberry]

NVIDIA Jetson

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

Docker

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

📖 Documentation

Document Description
Getting Started First steps with Industrial MCP
Configuration YAML configuration reference
Adapters Guide How to use protocol adapters
Custom Adapters Write your own adapter
Security Authentication and encryption
API Reference Complete API documentation

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Development Setup

# 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 .

Roadmap

  • Modbus TCP/RTU adapter
  • OPC UA adapter
  • MQTT adapter
  • Basic MCP server
  • Siemens S7 adapter (in progress)
  • Web dashboard
  • Local LLM integration (Ollama)
  • Anomaly detection ML models
  • ATEX certification support

🌍 Community


📜 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.


🏢 Enterprise Edition

Need more features for your enterprise?

Feature Open Source Enterprise
Core MCP Server
Modbus/OPC UA/MQTT
Community Support
Multi-site Management
Advanced Analytics Dashboard
Priority Support (SLA)
CE/ATEX Certification Kit
Custom Protocol Development

📧 Contact: enterprise@industrial-mcp.io


README mirrored from the source repository 5 months ago. The original is authoritative.

Questions

About EdgeAI MCP

How do I install EdgeAI MCP?

Run git clone https://github.com/xiao98/EdgeAI-MCP, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is EdgeAI MCP safe to use with an AI agent?

Its trust score is 34 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is EdgeAI MCP still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.