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The ongoing advances in multi-objective optimisation (MOO) are improving the way that complex real-world optimisation problems, mostly characterised by the definition of many conflicting objectives, are currently addressed. To put it into practice, developers require flexible implementations of these algorithms so that they can be adapted to the problemspecific needs. Here, metaheuristic optimisation frameworks (MOFs) are essential tools to provide end-user oriented development solutions. Even though consolidated MOFs are continuously evolving, they seem to have paid little attention to the new trends in MOO. Recently, new frameworks have emerged with the aim of providing support to these approaches, but they often offer less variety of basic functionalities like diversity of encodings and operators than other general-purpose solutions. In this paper we identify a number of relevant features serving to satisfy the requirements demanded by MOO nowadays, and propose a solution, called JCLEC-MOEA, on the basis of the JCLEC framework. As a key contribution, its architecture has been designed with a twofold purpose: reusing all the features already given by a mature framework like JCLEC, and extending it to enable new developments more flexibly than current alternatives.