As Artificial Intelligence (AI) is increasingly used in areas that impact human lives, concerns about fairness and transparency have grown, especially for protected groups. To better understand such concerns, explainability techniques can be leveraged not only for model interpretation but also to assess potential biases. The MIMOSA1 tool utilizes both individual and group explanation methods as bias detectors. It allows users to compare group fairness metrics with explanation findings, identify which features contribute to biased outcomes, visualize explanations through multiple perspectives and apply fairness interventions while tracking how feature contributions change. The tool is designed to be accessible to a wide audience of users, including sociologists, domain experts and machine learning practitioners.