SUMMARY: The Microbiome Community Detector (MiCoDe) software is a free user-friendly web tool that is designed to cluster a network of microbial taxa into communities using a Bayesian weighted stochastic block model. MiCoDe also filters the data automatically and accounts for the challenges of microbiome high-throughput sequencing data including high-dimensionality, compositionality, zero inflation, and nonlinearity. While MiCoDe is based on a rigorous statistical unsupervised learning model, our web tool can be easily used by any investigator. Users simply upload a csv file that contains their taxonomic abundance data where rows correspond to samples and columns correspond to taxa. Then, users make a few selections regarding data transformation, network estimation, and the number of communities in order to run the online analysis. If users are unsure of what selections to make, then they can opt for the default settings as these are our recommended settings. In this paper, we discuss the motivation, methodology, implementation, and results of MiCoDe. We also discuss how MiCoDe can be adapted by the user and how it may evolve over time. Our software is a valuable tool for microbiome community detection. AVAILABILITY AND IMPLEMENTATION: MiCoDe is freely available online at https://lce.biohpc.swmed.edu/micode/, does not require installation, and is not browser-specific. Users can also work locally using our R code, which is freely available on GitHub at https://github.com/klutz920/MiCoDe.