The SUCCESS project (Starting a User Community for Cutting-Edge Sequence Search) aims to improve how researchers access and work with large-scale genomic sequencing data. Most public repositories currently support only metadata-based search, which limits the reuse and reanalysis of existing data. The MetaGraph platform addresses this gap by enabling full-text search directly across raw sequencing data, making it substantially easier to identify relevant datasets across millions of samples. The project pursues two main goals: improving the MetaGraph platform's usability through expanded documentation and technical infrastructure, and building an active user community that can contribute feedback, share use cases, and support further development. Over the course of the project, the team has fully rebuilt the platform's website and documentation from the ground up, including walkthroughs and tutorials aimed at new users (WP1). The public index database has been expanded to over 27 million SRA samples, and a workflow system has been developed to help users construct their own MetaGraph indexes more easily (WP3). On the infrastructure side, the API has been hardened to support programmatic access across all query modes, and monitoring tools have been put in place to track query flow and user engagement (WP1, WP3). Community-building efforts have progressed through the launch of a Discord channel and consolidation of user feedback into a unified GitHub issue tracker (WP2). Partnerships have been initiated, including the AWS Open Data Sponsorship Program and outreach to research consortia (WP4). The platform has also been presented to multiple research communities, with further talks planned (WP5). Taken together, these developments position MetaGraph as an increasingly accessible and community-supported resource for large-scale genomic data reuse.