ThingsPanel MCP

ThingsPanel IoT Platform's MCP (Model Context Protocol) Server.

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🚀 Project Overview

ThingsPanel MCP Server is an innovative intelligent interface that enables you to:

• Interact with IoT devices using natural language

• Easily retrieve device information

• Monitor device performance and status in real-time

• Simplify device control commands

• Analyze platform-wide statistical data and trends

Related MCP server: ThingsBoard MCP Server

Target Audience

Intended Users

• IoT Solution Developers: Engineers and developers building solutions on the ThingsPanel IoT platform and seeking AI integration capabilities

• AI Integration Experts: Professionals looking to connect AI models with IoT systems

• System Administrators: IT personnel managing IoT infrastructure and wanting to enable AI-driven analysis and control

• Product Teams: Teams building products that combine IoT and AI functionality

Problems Addressed

• Integration Complexity: Eliminates the need to create custom integrations between AI models and IoT platforms

• Standardized Access: Provides a consistent interface for AI models to interact with IoT data and devices

• Security Control: Manages authentication and authorization for AI access to IoT systems

• Lowered Technical Barriers: Reduces technical obstacles to adding AI capabilities to existing IoT deployments

Ideal Application Scenarios

• Natural Language IoT Control: Enable users to control devices through AI assistants using natural language

• Intelligent Data Analysis: Allow AI models to access and analyze IoT sensor data for insights

• Anomaly Detection: Connect AI models to device data streams for real-time anomaly detection

• Predictive Maintenance: Enable AI-driven predictive maintenance by providing device history access

• Automated Reporting: Create systems that can generate IoT data reports and visualizations on demand

• Operational Optimization: Use AI to optimize device operations based on historical patterns

✨ Core Features

• 🗣️ Natural Language Querying

• 📊 Comprehensive Device Insights

• 🌡️ Real-time Telemetry Data

• 🎮 Convenient Device Control

• 📈 Platform-wide Analytics

🛠️ Prerequisites

• Python 3.8+

• ThingsPanel Account

• ThingsPanel API Key

📦 Installation

Option 1: Pip Installation

pip install thingspanel-mcp

Option 2: Source Code Installation

# Clone the repository
git clone https://github.com/ThingsPanel/thingspanel-mcp.git

# Navigate to project directory
cd thingspanel-mcp

# Install the project
pip install -e .

🔐 Configuration

Configuration Methods (Choose One)

Method 1: Direct Command Line Configuration (Recommended)

thingspanel-mcp --api-key "Your API Key" --base-url "Your ThingsPanel Base URL"

Method 2: Environment Variable Configuration

If you want to avoid repeated input, set environment variables:

# Add to ~/.bashrc, ~/.zshrc, or corresponding shell config file
export THINGSPANEL_API_KEY="Your API Key"
export THINGSPANEL_BASE_URL="Your ThingsPanel Base URL"

# Then run
source ~/.bashrc  # or source ~/.zshrc

💡 Tips:

• API keys are typically obtained from the API KEY management in the ThingsPanel platform

• Base URL refers to your ThingsPanel platform address, e.g., http://demo.thingspanel.cn/

• Command-line configuration is recommended to protect sensitive information

🖥️ Claude Desktop Integration

Add the following to your Claude desktop configuration file (claude_desktop_config.json):

{
  "mcpServers": {
    "thingspanel": {
      "command": "thingspanel-mcp",
      "args": [
        "--api-key", "Your API Key",
        "--base-url", "Your Base URL"
      ]
    }
  }
}

🤔 Interaction Examples

Using the ThingsPanel MCP Server, you can now make natural language queries such as:

• "What is the current temperature of my sensor?"

• "List all active devices"

• "Turn on the automatic sprinkler system"

• "Show device activity for the last 24 hours"

🛡️ Security

• Secure credential management

• Uses ThingsPanel official API

• Supports token-based authentication

License

Apache License 2.0

🌟 Support Us

If this project helps you, please give us a star on GitHub! ⭐