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This research investigates the impact of the digital economy on high-quality agricultural development, specifically its impact on Agricultural Green Total Factor Productivity (AGTFP). The research combines Dynamic Qualitative Comparative Analysis (QCA) and Necessary Condition Analysis (NCA) methods on data from 31 provinces in China between 2011 and 2023. The study produces the following results, (1) A single element of the digital economy is not a necessary condition for improving AGTFP. The driving effect relies on the interactions of multiple elements. Configuration analysis indicates viable driving paths to AGTFP, resulting in four effective driving paths, including financial-government dual-driver model path, infrastructure-government dual-driver model path，financial-resource dual-driver model path and industry-led driver model path. (2) The paths to achieving high-quality agricultural development vary among different regions. The eastern region places more emphasis on the integration of finance and policy, while the central and western regions stress the synergy between infrastructure and the government. (3) The pathways are stable with respect to time. The most notable realization is that digital finance pathways show higher overall constancy for the years of study and have a temporal stability of greater than 0.85 in most years. This study combines the TOE framework with configuration analysis, expanding the theoretical framework of agricultural digitalization, revealing the key paths for the digital economy to promote the development of green agriculture, and providing empirical evidence for formulating differentiated digital agriculture policies.