A comprehensive Model Context Protocol (MCP) server that provides Internet of Things (IoT) device integration for AI assistants like Claude Desktop and Cursor IDE. This server enables AI to read sensor data from IoT devices and dispatch data collection tasks to IoT devices through a unified interface.
{
"mcpServers": {
"iot-mcp-servers": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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A comprehensive Model Context Protocol (MCP) server that provides Internet of Things (IoT) device integration for AI assistants like Claude Desktop and Cursor IDE. This server enables AI to read sensor data from IoT devices and dispatch data collection tasks to IoT devices through a unified interface.
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
License not specified.
Is it maintained?
Last commit 195 days ago. 10 stars.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
This server is missing a description. Tools and install config are also missing.If you've used it, help the community.
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A comprehensive Model Context Protocol (MCP) server that provides Internet of Things (IoT) device integration for AI assistants like Claude Desktop and Cursor IDE. This server enables AI to read sensor data from IoT devices and dispatch data collection tasks to IoT devices through a unified interface.
[DEMO_URL]
IoT MCP Server demonstration showing sensor data reading, device task assignment, and real-time monitoring
Before using this MCP server, you need to install the following components:
bashpython --version
# or
python3 --version
Installation:
Windows: Download from python.org macOS: Download from python.org or use Homebrew: brew install python Linux: Usually pre-installed, or install via package manager: sudo apt install python3 python3-pip
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Alternative Installation Methods:
# Using pip
pip install uv
# Using Homebrew (macOS)
brew install uv
# Using cargo (if you have Rust installed)
cargo install --git https://github.com/astral-sh/uv uv
Verify Installation:
bashuv --version
git clone [PLACEHOLDER_REPOSITORY_URL]
cd iot-mcp-server
That's it! The project uses uv for dependency management, which will automatically handle all Python dependencies when the server runs.
Connect MCU and Sensors:
Network/Serial Connection:
Navigate to Sensor Directory:
# Example for MPU6050 sensor
cd sensors/MPU6050
Run Sensor Configuration:
python config.py
This will configure the sensor parameters and generate the necessary configuration files.
Upload Main Script to MCU:
# Use mpremote to transfer main.py to your MCU
mpremote connect [PORT] cp main.py :
Replace [PORT] with your MCU's serial port (e.g., /dev/ttyUSB0 on Linux, COM3 on Windows, /dev/tty.usbserial-* on macOS).
Alternative upload methods:
# For ESP32/ESP8266
mpremote connect /dev/ttyUSB0 cp main.py :
# For Raspberry Pi Pico
mpremote connect /dev/ttyACM0 cp main.py :
Initialize and Configure MCP Server:
# Initialize uv project (if not already done)
uv init .
# Add MCP dependencies
uv add "mcp[cli]"
This will set up the MCP server with all necessary dependencies.