Microbial communities play crucial roles in multiple natural and engineered environments, contributing to biogeochemical cycling, waste treatment, and biotechnological processes. Much like for single organisms, genome-scale metabolic models (GEMs) have become essential in contextualizing, designing and optimizing microbiomes. Computational modeling of microbial community metabolism provides valuable insights into community dynamics, interactions, and metabolic capabilities. Here, we present a comprehensive protocol for describing and engineering microbial community metabolic models in silico, leveraging FLYCOP (FLexible sYnthetic Consortium Optimization). Starting with available individual GEMs, this protocol covers the construction of condition-specific GEMs for community members, the generation of community-based metabolic models, and the analysis of community-wide metabolic capabilities and interactions. Furthermore, we showcase the utility of FLYCOP by illustrating its application in: (i) describing a community-driven complex biological process (e.g., denitrification) and (ii) designing a synthetic community for biotechnological purposes (e.g., production of violacein).