The Easiest Way to Use MQTT: A Hands-On Demo with Harper’s Built-In Broker

‍The full source code demonstrated in the video is available here: https://github.com/HarperFast/mqtt-getting-started

MQTT has become one of the most widely adopted protocols for real-time messaging in IoT and distributed systems. Its lightweight footprint, simple publish–subscribe pattern, and resilience in unreliable network environments make it a natural choice for sensors, edge devices, and telemetry workloads. But while MQTT is powerful, setting up and managing a broker, handling authentication, storing messages, and integrating data into applications can quickly become more complex than developers expect.

In this week’s episode, Ivan walks through the fundamentals of MQTT—what it is, how it works, and how Harper dramatically simplifies the developer experience by including MQTT natively inside its unified application platform.

MQTT consists of two core components: clients and a broker. Clients publish messages to topics, and other clients subscribe to those topics to receive data. This Pub/Sub model enables decoupled, scalable real-time communication. MQTT also supports useful features such as Quality of Service (QoS) levels for delivery guarantees and retained messages for storing the most recent data on a topic.

Where Harper really shines is in how effortlessly it integrates this protocol into the platform. When you install and run Harper, MQTT is already enabled out of the box—no configuration, provisioning, or third-party services required. The broker runs on the standard MQTT ports, supports authentication by default, and includes WebSocket capabilities for modern applications. Developers can begin publishing and subscribing immediately using any MQTT client or library in languages like JavaScript, Python, or even command-line tools.

Even more compelling is Harper’s ability to persist retained messages directly into a table. In the example from the video, a simple temperature sensor publishes readings to a topic. When retained mode is enabled, Harper automatically stores each message in a sensors table—no extra wiring, no additional database setup. This makes it possible to combine real-time streams with long-term storage, analysis, and alerting using the same platform.

Harper’s built-in MQTT support allows developers to build IoT, AI-at-the-edge, and event-driven systems in minutes rather than days. With one small, unified runtime providing database, caching, messaging, and application logic, it removes the complexity of managing multiple services and lets you focus on building meaningful real-time experiences.

If you’re exploring MQTT or building sensor-driven applications, this demo shows just how much faster—and simpler—the process can be with Harper. Check out the video and follow along with the sample code to get started.

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