Software agents and multi-agent systems are critical components in the development of distributed autonomous systems, as they exhibit a wide range of “intelligence”, from reactive behaviours to advanced reasoning and planning. Integrating these capabilities into multi-agent systems enables distributed artificial intelligence, a programming paradigm in which autonomous entities work together efficiently across a network to achieve shared goals. Another important aspect we consider in this work is represented by the disruptive impact of 5G technology, which is moving computation to the edge of the network. As a result of this shift, embedded devices with microcontrollers – which are renowned for their low power consumption and limited computing power – have proliferated. This paradigm fits in well with the small cooperating entities scattered across the network in this situation but, at the same time, it is difficult to provide agent platforms for embedded devices, though. Indeed, the most recent state-of-the-art MAS platforms, which are primarily Java-based, raise issues with microcontroller speed and memory overhead. To achieve this goal, we designed and implemented an ecosystem, entirely written in C++, to create multi-agent systems in an actual Internet of Things setting. Our ecosystem is compounded by Democle, a logic/declarative agent programming framework, and Hermes, a unified wireless network interface, both specifically created for embedded systems. In this paper, we describe our ecosystem’s functionality, architecture, and benefits of use. In addition, we provide a case study and a few experiments to prove how our platform works and its efficiency in terms of overhead.