A robust integration to control Meshtastic LoRa nodes via USB for secure, off-grid mesh communication and automated monitoring.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install meshtastic-skill
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install meshtastic-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Meshtastic Skill?
This skill enables your AI agent to interface directly with Meshtastic hardware, providing a bridge between local LoRa mesh networks and your digital workspace. By connecting compatible hardware via USB, you can send texts, check network status, and monitor incoming traffic from peers without relying on traditional internet infrastructure.
It leverages a Python-based bridge service to handle serial communication, socket commands, and MQTT integration, making it a robust choice for users interested in decentralization and off-grid reliability. As part of the Openclaw Skills ecosystem, it allows for sophisticated automation of mesh messaging and long-range communication tracking.
Meshtastic Skill Use Cases
- Sending off-grid emergency alerts or status updates via LoRa radio.
- Monitoring local mesh network health and node positions in real-time.
- Building automated bridges between internet-based platforms and the mesh network.
- Collecting long-range sensor data or telemetry transmitted over the Meshtastic protocol.
- Managing high-volume mesh traffic and filtering noise via AI-driven summaries.
How Meshtastic Skill Works
- Connect a Meshtastic-compatible radio (such as a RAK4631 or T-Beam) to your host machine via a stable USB connection.
- The Python bridge service establishes a serial connection to the hardware and opens a local socket on port 7331 for command processing.
- The bridge optionally connects to an MQTT broker to synchronize global mesh traffic with local message logs.
- Incoming messages from the mesh are logged to the local file system for analysis.
- Your AI agent reads these logs or executes socket commands to interact directly with the mesh network.
Meshtastic Skill Setup
Ensure you have Python 3.9+ installed along with the required dependencies. Use the following steps to get started with this component of Openclaw Skills:
# Install required Python packages
pip install meshtastic paho-mqtt
# Configure your node details in CONFIG.md, then start the bridge
sudo systemctl enable meshtastic-bridge
sudo systemctl start meshtastic-bridge
# Verify the connection via socket
echo '{"cmd":"status"}' | nc -w 2 127.0.0.1 7331
Meshtastic Skill Data Schema & Taxonomy
The skill organizes its operational data and logs using the following structure:
| File Path | Description |
|---|---|
/tmp/mesh_messages.txt |
Pipe-delimited log containing TIMESTAMP|CHANNEL|SENDER|DISTANCE|TEXT. |
/tmp/mesh_nodes.json |
Cached metadata regarding detected node positions and hardware IDs. |
~/.openclaw/skills/meshtastic/CONFIG.md |
User-defined configuration for MQTT and local serial ports. |
Meshtastic Skill Advanced Features
- Automated monitoring via cron jobs to trigger alerts based on message content.
- Periodic digest generation to summarize mesh activity over custom time windows.
- Dynamic map visibility toggling and forced position reporting for geolocation tracking.
- Intelligent noise filtering using AI to separate human communication from automated 'Hello' pings.
- Seamless integration with regional frequency configurations (868 MHz / 915 MHz) within the Openclaw Skills framework.
SKILL.md
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