A precise understanding of the carbon dynamics of agricultural land use is essential for advancing China’s “dual carbon” goals and promoting sustainable rural development. Drawing on panel datasets for 31 Chinese provinces over the period 1997–2022, this study comprehensively analyzes the spatiotemporal evolution, regional disparities, and transition dynamics of agricultural carbon capture and emissions. Using a combination of the emission factor method, the Dagum Gini coefficient, kernel density estimation, and Markov chain models, the study finds that China’s total agricultural carbon capture has continued to increase, yet regional disparities are widening, with the central region leading and the northeastern region lagging. Meanwhile, agricultural carbon emissions exhibit a “strong west, weak east” spatial pattern and demonstrate a high degree of club convergence. Club convergence refers to the phenomenon where regions with similar initial levels converge to the same steady-state over the long run, while remaining persistently different from other regions. The net carbon effect exhibits a dual structure of carbon surplus zones and carbon deficit zones: 23 provinces act as carbon surplus zones, while 8 provinces are carbon deficit zones, primarily located in ecologically fragile or special-function regions. These findings highlight the spatial heterogeneity, path dependence, and policy sensitivity of carbon effects from agricultural land use. Accordingly, the study proposes differentiated policy recommendations, including region-specific carbon management strategies, the establishment of a unified agricultural carbon trading system, and the integration of technological and institutional innovations to achieve a balanced and low-carbon agricultural transformation.