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Brain-Computer Interfaces (BCI) give rise to a communication means between individuals with severe motor disorders, and their external world via the measurement of the electroencephalographic (EEG) activity. BCI users may control this activity by concentrating on a specific mental task. Motor imagery (MI) executions have become the most used mental task by BCI-groups. Despite a large number of references describing the theoretical framework of MI-based BCIs, there is not enough information related to the available computer software that could be suitable to develop a specific-purpose, efficient and straightforward BCI. Therefore, the aims of this paper are: (1) to develop a MI-based BCI system making use of Python programming language, and (2) to study MI signals of three users via the proposed BCI system in order to adapt a computer for posterior applications. The use of Python along with plug-ins for developing MI-based BCI systems is not only feasible, but also it is proficient. Moreover, the Python community provides extensive variety of tools to design compelling systems.