As the severity of climate change escalates, agriculture, being one of the primary contributors to global carbon emissions, has progressively come under scrutiny. Thus, fostering a low-carbon agriculture system is paramount in achieving the ambitious “dual carbon” goals of reaching peak carbon and attaining carbon neutrality. This study engages urban panel data from the Yellow River Basin spanning 2001-2020 to compute the agricultural carbon emissions therein. The research harnesses a spatial Durbin model to probe the influencing mechanisms and spatial effects while examining the implications of agricultural mechanization on such emissions. The findings reveal: (1) From a spatiotemporal perspective, total agricultural carbon emissions within the Yellow River Basin exhibited an oscillating “M”-shaped pattern. Upon analyzing spatial patterns, the carbon emissions were highest downstream, moderate midstream, and least upstream, signifying pronounced regional disparities. (2) Concerning the causal elements, agricultural mechanization, from a direct effects standpoint, tends to somewhat diminish local agricultural carbon emissions. Regarding spillover effects, agricultural mechanization similarly represses carbon emissions in adjacent locales. (3) Heterogeneity analysis suggests that in the midstream cities, agricultural mechanization results in a significant decrease in agricultural carbon emissions. Contrarily, upstream and downstream cities witness a stimulating effect. At present, with China's agricultural economy navigating intense environmental pressure, these insights lend invaluable support to practices aimed at curbing agricultural carbon emissions. By shedding light on the interaction between agricultural mechanization and carbon emissions, they offer a novel perspective and empirical data. In turn, these can contribute to formulating policies that seek to reignite rural areas while concurrently striving to meet the strategic objectives of peak carbon and carbon neutrality.