Coastal tropical cyclones are high-impact events whose nearshore wind structures are difficult to observe with conventional observing systems alone. Available SAR wind products are commonly distributed as scene-level products rather than organized cyclone-focused event records. This fragmentation limits reproducibility, makes quality screening repetitive, and obscures the relationship among storm identity, scene geometry, coastal context, and derived wind fields. We present TC-SARCoast, a global event-based Sentinel-1 Level-1 Interferometric Wide Swath (IW) SAR dataset for coastal tropical cyclones from 2015 to 2026. The current release contains 277 tropical-cyclone (TC) events, 411 event-track directories, and 3128 SAR scenes. The dataset is organized into four traceable layers: L0 scene provenance and source linkage, L1 SAR–IBTrACS matchup records, L2 scene-level statistics and hierarchical scene-usability classes, and L3 value-added wind-product files. We develop an event-track-scene data model that preserves provenance, storm context, coastal information, scene usability, and product diagnostics in one hierarchy. Dataset assessment includes completeness and consistency assessment, spatiotemporal coverage analysis, scene-quality statistics, external validation against SFMR, NDBC, and SMAP, and wind-regime-dependent comparison with ECMWF fields. Validation against SFMR aircraft observations demonstrates that the released approximately 1 km L3 wind product captures tropical-cyclone wind fields with high matchup consistency, achieving an RMSE of 3.97 m s^−1, bias of -0.36 m s^−1, and correlation of 0.82 for the quality-screened matchup sample. TC-SAR-Coast advances SAR tropical- cyclone data use from isolated scene inspection to reproducible event-based analysis by integrating source provenance, storm context, coastal exposure information, quality diagnostics, validation records, and value-added wind fields in a single open archive.