The JCVI library is a versatile Python-based toolkit designed for comparative genomics analysis, offering a suite of tools that excel in genome assembly, annotation, and comparative genomics. It features a modular design, providing high-level utilities for tasks such as format parsing, graphics generation, and manipulation of genome assemblies and annotations. The library supports genomics algorithms like MCscan and ALLMAPS, which are widely used in building genome releases and producing publication-ready figures for quality assessment and evolutionary inference. Developed and maintained collaboratively, the JCVI library emphasizes quality and reusability. JCVI includes modules for comparative genomics, such as MCscan for synteny inference and visualization, and ALLMAPS for map-based assembly and alignment. It also provides tools for genome features and landscape plotting, genome-build quality control, and pedigree and genome diversity analysis. The library is accessible via GitHub and has gained significant popularity, with over 220,000 downloads to date. It supports a wide range of bioinformatics tasks, including genome assembly, annotation, and visualization, and is designed to streamline genomic data manipulation and analysis. The JCVI library is modular, with utilities for bioinformatics format parsing, graphics generation, and exploratory tools linking the pillars of assembly, annotation, and comparative genomics. It provides a simple command line interface for users to interact with its tools, making it accessible for researchers. The library is particularly useful in plant genomics where polyploidy and high levels of genetic variation pose significant challenges to assembly. It also supports the integration of multiple types of mapping data, enhancing the ability to construct accurate genome assemblies even in complex scenarios. The JCVI library is a powerful resource for scientists to address complex genomic data analysis and visualization challenges. It has been widely adopted in the bioinformatics community and is expected to continue evolving with community feedback and the latest genomic discoveries. The library's collaborative development and emphasis on quality and reusability make it a valuable tool for comparative genomics research.The JCVI library is a versatile Python-based toolkit designed for comparative genomics analysis, offering a suite of tools that excel in genome assembly, annotation, and comparative genomics. It features a modular design, providing high-level utilities for tasks such as format parsing, graphics generation, and manipulation of genome assemblies and annotations. The library supports genomics algorithms like MCscan and ALLMAPS, which are widely used in building genome releases and producing publication-ready figures for quality assessment and evolutionary inference. Developed and maintained collaboratively, the JCVI library emphasizes quality and reusability. JCVI includes modules for comparative genomics, such as MCscan for synteny inference and visualization, and ALLMAPS for map-based assembly and alignment. It also provides tools for genome features and landscape plotting, genome-build quality control, and pedigree and genome diversity analysis. The library is accessible via GitHub and has gained significant popularity, with over 220,000 downloads to date. It supports a wide range of bioinformatics tasks, including genome assembly, annotation, and visualization, and is designed to streamline genomic data manipulation and analysis. The JCVI library is modular, with utilities for bioinformatics format parsing, graphics generation, and exploratory tools linking the pillars of assembly, annotation, and comparative genomics. It provides a simple command line interface for users to interact with its tools, making it accessible for researchers. The library is particularly useful in plant genomics where polyploidy and high levels of genetic variation pose significant challenges to assembly. It also supports the integration of multiple types of mapping data, enhancing the ability to construct accurate genome assemblies even in complex scenarios. The JCVI library is a powerful resource for scientists to address complex genomic data analysis and visualization challenges. It has been widely adopted in the bioinformatics community and is expected to continue evolving with community feedback and the latest genomic discoveries. The library's collaborative development and emphasis on quality and reusability make it a valuable tool for comparative genomics research.