**Abstract:** Gene Ontology (GO) is widely used for gene functionality description and functional annotation. This paper introduces agriGO, an integrated web-based GO analysis toolkit specifically designed for the agricultural community. agriGO builds upon the successful EasyGO tool, enhancing its performance and accessibility. The system supports 38 agricultural species and 274 data types, expanding the range of supported organisms and gene identifiers. agriGO offers flexible user input, allowing user-defined reference and annotation. It introduces new analysis approaches, including Gene Set Enrichment Analysis (GSEA) strategies and customizable features. Four integrated tools—SEA, PAGE, BLAST4ID, and SEACOMPARE—are provided to meet diverse analytical needs. agriGO also functions as a GO data repository, offering search and download capabilities. The toolkit is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/. **Introduction:** High-throughput techniques generate large datasets of gene expression values, necessitating advanced analysis tools like GO enrichment analysis. agriGO retains the advanced features of EasyGO while adding new functionalities. It supports multiple statistical methods for enrichment analysis and provides enhanced graphical presentations, including hierarchical tree graphs and flash bar charts. Cross-comparison of results from different datasets is facilitated, aiding in the interpretation of complex experiments. agriGO supports a wide range of agricultural species and identifiers, and offers a BLAST service for ID mapping. The web interface is user-friendly, with interactive help and flexible input requirements. **Discussion:** agriGO aims to provide better service to EasyGO users, ensuring consistent analysis conclusions. It addresses issues such as GO term overrepresentation and GO annotation coverage. The toolkit has been tested and maintained, facilitating researchers in the agricultural community to extract biological insights from high-throughput data.**Abstract:** Gene Ontology (GO) is widely used for gene functionality description and functional annotation. This paper introduces agriGO, an integrated web-based GO analysis toolkit specifically designed for the agricultural community. agriGO builds upon the successful EasyGO tool, enhancing its performance and accessibility. The system supports 38 agricultural species and 274 data types, expanding the range of supported organisms and gene identifiers. agriGO offers flexible user input, allowing user-defined reference and annotation. It introduces new analysis approaches, including Gene Set Enrichment Analysis (GSEA) strategies and customizable features. Four integrated tools—SEA, PAGE, BLAST4ID, and SEACOMPARE—are provided to meet diverse analytical needs. agriGO also functions as a GO data repository, offering search and download capabilities. The toolkit is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/. **Introduction:** High-throughput techniques generate large datasets of gene expression values, necessitating advanced analysis tools like GO enrichment analysis. agriGO retains the advanced features of EasyGO while adding new functionalities. It supports multiple statistical methods for enrichment analysis and provides enhanced graphical presentations, including hierarchical tree graphs and flash bar charts. Cross-comparison of results from different datasets is facilitated, aiding in the interpretation of complex experiments. agriGO supports a wide range of agricultural species and identifiers, and offers a BLAST service for ID mapping. The web interface is user-friendly, with interactive help and flexible input requirements. **Discussion:** agriGO aims to provide better service to EasyGO users, ensuring consistent analysis conclusions. It addresses issues such as GO term overrepresentation and GO annotation coverage. The toolkit has been tested and maintained, facilitating researchers in the agricultural community to extract biological insights from high-throughput data.