
lwsinclair/iot-edge-mcp-server
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MCP server for Industrial IoT, SCADA and PLC systems. Unifies MQTT sensors, Modbus devices and industrial equipment into a single AI-orchestrable API.
개요
This server transforms industrial infrastructure into an AI-orchestrable system, exposing 11 powerful tools for complete IoT/SCADA/PLC control via HTTP endpoints. Perfect for AI-driven industrial automation, predictive maintenance, and smart factory operations. - - Unified interface for industrial systems: - MQTT for wireless IoT sensors and actuators - Modbus TCP/RTU for PLC and industrial devices - Time-series data with InfluxDB integration - Real-time caching with Redis - Simulated mode for testing without hardware - - Monitor and analyze industrial data: - Real-time sensor readings (temperature, pressure, flow, etc.
README
원문 README의 일부입니다. 원문 보기.
IoT/Edge MCP Server
Model Context Protocol (MCP) server for Industrial IoT, Edge Computing and Automation
This server transforms industrial infrastructure into an AI-orchestrable system, exposing 11 powerful tools for complete IoT/SCADA/PLC control via HTTP endpoints. Perfect for AI-driven industrial automation, predictive maintenance, and smart factory operations.
✨ Features
-
🏭 Multi-Protocol Support - Unified interface for industrial systems:
- MQTT for wireless IoT sensors and actuators
- Modbus TCP/RTU for PLC and industrial devices
- Time-series data with InfluxDB integration
- Real-time caching with Redis
- Simulated mode for testing without hardware
-
📊 Complete Sensor Management - Monitor and analyze industrial data:
- Real-time sensor readings (temperature, pressure, flow, etc.)
- Historical data with aggregations (mean, max, min)
- Multi-sensor batch operations
- Quality indicators and signal monitoring
-
⚡ Actuator Control - Command industrial equipment:
- Valve control (open/close)
- Motor management (start/stop/speed)
- Pump operations
- PLC register manipulation
-
🚨 Alarm System - Enterprise-grade monitoring:
- Multi-priority alarms (LOW, MEDIUM, HIGH, CRITICAL)
- Automatic threshold monitoring
- Alarm acknowledgment tracking
- Real-time notifications
-
🔒 Production Features - Enterprise-ready:
- Rate limiting for command safety
- Comprehensive error handling
- Connection pooling and auto-reconnect
- Full audit logging
- Thread-safe operations
🚀 Quick Start
Installation
# Clone the repository
git clone https://github.com/llm-use/iot-mcp-server.git
cd iot-mcp-server
# Install dependencies
pip install -r requirements.txt
# For testing without hardware, use simulation mode
pip install -r requirements-sim.txt
Starting the Server
Option 1: Simulation Mode (No Hardware Required)
python IoT_mcp_sim.py
Option 2: Production Mode (Real Hardware)
# Configure your devices in iot_config.yaml
# Start required services (MQTT, InfluxDB, Redis)
docker-compose up -d
# Start the server
python IoT_mcp.py
Server will start on http://localhost:8000
🤖 Using with PolyMCP
This MCP server is designed to work seamlessly with PolyMCP - a powerful framework for orchestrating MCP servers with AI agents.
Example: AI-Controlled Industrial System
#!/usr/bin/env python3
import asyncio
from polymcp.polyagent import UnifiedPolyAgent, OllamaProvider
async def main():
# Initialize your LLM provider
llm = OllamaProvider(model="gpt-oss:120b-cloud", temperature=0.1)
# Connect to IoT MCP server
agent = UnifiedPolyAgent(
llm_provider=llm,
mcp_servers=["http://localhost:8000/mcp"],
verbose=True
)
async with agent:
print("✅ IoT MCP Server connected!\n")
설치
This server does not publish a one-line install command.
Open the repository installation guide MCP 초보자라면? mcpskill.org 가이드부터 시작하세요 →