MonsterMQ can run AI Agents – triggered by MQTT topics or on a schedule, with direct access to broker data in the context, and support for MCP Servers (including the internal one).

The agent can publish data to other topics – and that can trigger the next little agent. 🔄

Is this a good idea? Honestly, I don’t know yet – this is purely for learning right now.

The broker now has a NATS bridge integrated – you can receive messages from NATS and also publish to NATS.

For example, with simple wildcard subscriptions you can bring your topics straight into NATS – no extra glue code needed!

A big thanks to Kevin Joosten for this contribution!

‼️ And I added that MMQ can act as a NATS Server (NATS core 1.0). So, now NATS clients can connect to MonsterMQ and pub/sub to topics. NATS protocol is super simple.

This opens up some new integration scenarios where MQTT and NATS need to coexist in the same architecture.

Star it if you like it – and drop me a message if you’re using MonsterMQ in your setup!

I’ve added a first version a workflow engine that lets you define custom business logic directly inside the broker:
🔹 React on multiple input topics
🔹 Write your logic in JavaScript, more functions
🔹 Publish results to output topics

💾 And there is now a JDBC-based Data Logger with store and forward.

It currently supports JSON payloads, with a JSON schema, you can define how fields map to columns in your database tables.

See the pictures, a simple test with 30 Python clients publishing topics to the broker. It stores 20 kHz of data into a QuestDB instance without issues.

It’s a simple way to process and store data where it flows – no need for external services or function frameworks.

👉 MonsterMQ.com 👉 give a star on GitHub if you like it. thx.

I’ve merged the functionality for bringing MQTT UNS topic trees to Neo4j. Previously part of my Automation-Gateway open source project.

👉 Now, MonsterMQ can push namespaces from the broker into a Neo4j graph database.

💡 Graph databases can help LLMs understand context and relationships better. This integration makes it easy to link your UNS data with other graph data, enriching the context of your factory and process information.

⚠️ But be careful – don’t overload your database with too many writes 😉

👉 MonsterMQ.com 👉 Open-Source!

💬 Yesterday a client asked me:

“Generally, another important element is ACLs — but in a way that I can select topics easier with a GUI instead of using only wildcards, since I need very granular ACLs.”

☕️ I decided to implement it – my date with a lovely woman got canceled today, by her 🤨, so I suddenly had some extra time.

It was straightforward – almost everything in MonsterMQ can be configured through its GraphQL API, so building such a page was easy.

Now, ACL management just got a lot more user-friendly.

⚙️ Next up: I’m working on a lightweight flow engine, so transformations can be implemented directly in the broker – in JavaScript, but still running where the data flows.

👉 MonsterMQ.com