Like research data, research software plays a crucial role in the reproducibility of scientific results, and is therefore increasingly recognised as a research output in itself. The development of research software (ranging from data-specific scripts to standalone software products) can be a major project that requires good planning and management. For example, the necessary infrastructure, such as software dependencies or hardware requirements, must be addressed, as well as the human resources needed to develop and maintain the software and write its documentation. Software Management Plans (SMPs) document all these requirements and thus improve software quality and reusability, in a similar way as Data Management Plans (DMPs) enhance research data. The Research Data Management Organiser (RDMO) is a well-established tool for creating DMPs and SMPs among the research community . The structured information in SMPs is often useful in other contexts and stages of the software project and should be reusable, for example by being shareable with other tools, such as GitHub/GitLab. The other way round, information stored in resources such as GitHub/GitLab could be used to create or update an SMP. In our project "Machine-AUtomated Support for Software Management Plans" (MAUS), we are developing plugins for RDMO that enhance the machine-readability and -actionability of SMPs by enabling the exchange of project information from and to the SMP. In our demo session, we will present the current state of our project plugins. We look forward to hearing your comments and ideas, and to discussing with you which further features and interfaces we should implement.