A real-time data streaming connector that pipes MQTT, Kafka, and webhook data directly into AI agents via the Model Context Protocol.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install justinx
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 justinx 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 justinx?
justinx is a powerful bridge between real-time data sources and AI agents. It allows developers to ingest live streams from IoT sensors, industrial telemetry, and cloud events into their AI-driven workflows. By leveraging Openclaw Skills, users can transform static AI models into dynamic systems capable of monitoring live environments and responding to streaming events.
The skill simplifies complex integrations with MQTT brokers and Kafka clusters, providing a unified interface for data ingestion and processing. Furthermore, it offers built-in support for automated alerting and anomaly detection, ensuring that agents can proactively manage data-driven triggers without manual intervention.
justinx Use Cases
- Monitoring IoT sensors and industrial telemetry via MQTT brokers in real-time.
- Consuming high-volume event data from Kafka topics for immediate analysis by an AI agent.
- Creating webhook endpoints to receive pushed data from third-party services and cloud triggers.
- Building live dashboards with embedded WebSocket URLs for real-time visualization in generated apps.
- Implementing automated alerting and anomaly detection on streaming data for proactive system maintenance.
How justinx Works
- Establish a connection to a data source such as an MQTT broker, Kafka cluster, or a dedicated Webhook endpoint.
- Use the AI agent to sample live entries or backfill historical data from the stream to provide context.
- Configure watchers to monitor the data stream for specific conditions, thresholds, or anomalies defined by JSON configurations.
- Retrieve WebSocket URLs to pipe the live data into frontend applications, allowing the agent to build interactive dashboards.
- Manage and update stream configurations or watcher scripts dynamically through the MCP tool interface.
justinx Setup
1. Get an API key
Sign up at https://justinx.ai and copy your API key from Dashboard > Settings.
2. Configure the MCP server
Add justinx as an MCP server. You can add it directly to your configuration file (e.g., ~/.openclaw/openclaw.json):
{
"mcpServers": {
"justinx": {
"url": "https://api.justinx.ai/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}
3. Setup via mcporter
If you have the mcporter skill installed, you can use the following command:
mcporter add justinx --url https://api.justinx.ai/mcp --header "Authorization: Bearer YOUR_API_KEY"
justinx Data Schema & Taxonomy
The justinx skill organizes data through Connections and Watchers, utilizing a standardized message format for all streams.
| Entity | Description | Key Fields |
|---|---|---|
| Connection | A stream source (MQTT, Kafka, Webhook) | type, broker, topics, ingestUrl, webSocketUrl |
| Stream Entry | A single data point in the stream | id, fields (topic, payload), ts |
| Watcher | A managed automation script | connectionId, config (JSON), status, logs |
| WebSocket | Real-time message format | type (backfill/entry), entries, ts |
All stream entries follow a standard JSON format: {"id": "...", "fields": { "topic": "...", "payload": "..." }, "ts": 1234567890}.
justinx Advanced Features
- Automated anomaly detection and threshold alerting via managed watchers that run continuously in the background.
- WebSocket URL generation for seamless integration with React, Next.js, or mobile apps without needing a custom SDK.
- Multi-topic filtering on WebSocket streams using URL parameters to optimize bandwidth and focus.
- Persistent watcher processes with automatic restarts, crash reporting, and accessible stdout/stderr logs.
- Secure connectivity support for enterprise environments, including TLS, SASL, and SSL for broker authentication.
- Seamless integration with Openclaw Skills to enable multi-agent collaboration on live telemetry data.
SKILL.md
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