Genome-scale metabolic models (GEMs) are essential tools in systems biology, enabling the mathematical simulation of metabolic pathways encoded in genomes to predict phenotypes and community interactions. However, the complexity of GEMs often limits the interpretation and comparison of their outputs. To address these challenges, we present MMINT (Metabolic Modelling Interactive Network Tool), designed to facilitate the exploration and comparison of metabolic networks. MMINT leverages GEM networks and flux solutions from Constraint Based Analysis (e.g., Flux Balance Analysis) to create interactive visualizations. This tool allows for seamless toggling of metabolites and reactions, network decluttering, pathway tracing, and highlights similarities and differences between metabolic states. This, in turn, enhances network exploration and the identification of mechanistic drivers of phenotypes under different environmental conditions. We demonstrate MMINT’s applicability to microbial ecology using a GEM of the butyrate producer Caprococcus comes ATCC 27758. MMINT a) shows how this metabolic network is predicted to adapt to the presence of a second butyrate producer, Eubacterium rectale ATCC 33656, and b) facilitates the identification of mechanistic drivers that impact butyrate production in co-culture. By providing an intuitive and responsive model-exploration experience, MMINT addresses the need for a tool that simplifies the interpretation of GEM outputs and promotes the understanding of metabolic interactions.