Public transport accessibility is central to evaluating the performance, equity, and efficiency of urban transit systems. However, mainstream assessments remain supply-centric and largely static, overlooking how service provision aligns with spatiotemporally varying travel demand. We propose a multiscale evaluation framework that integrates supply–demand synergy and apply it to Zhuhai’s central district (China). Using mobile phone signaling records from April 2023 and public transport data collected in June 2023, we examine spatial heterogeneity and the spatial matching between accessibility and travel demand at both citywide and local scales. Methods include the Gini coefficient, bivariate spatial autocorrelation, and a coupling-coordination model. Results show that (1) at the citywide scale, high-accessibility areas account for 34.1% of the land but cover 69.1% of travelers. Gini and Moran’s I indicates relatively equitable provision and significant spatial clustering between accessibility and trip volume. (2) At the local scale, a prominent “low accessibility–high demand” mismatch emerges, indicating weak supply–demand coordination in parts of the study area. (3) Policy suggestions are proposed to recalibrate stop locations, headways, and route supply to improve matching. The framework advances a more comprehensive understanding of the interplay between accessibility and demand, and offers decision support for optimizing urban transport planning.