The annotations of MGCs and BGCs are valuable for identifying metabolic pathways. This helps to provide more evidence for interactions between microbes and their associated primary or secondary metabolites. MGCs are predicted by gutSMASH [Ref: Nucleic Acids Research, 49.W1 (2021), W263–W270] while BGCs are generated by antiSMASH [Ref: Nucleic Acids Research, 51.W1 (2023), W46–W50]. Using hidden Markov models (pHMMs), these two algorithms perform comparative genomic analysis with two customized databases, KnownClusterBlast and ClusterBlast, to MGCs or BGCs from microbial genomes. Due to the lack of strain-level reference genomes, species-level reference genomes of microbes within each genus from MASI database are downloaded from NCBI for analysis. Finally, we display the related compounds as substrates or products of each MGC or BGC with a similarity percentage of 100% calculated by KnownClusterBlast.