How patterns in community diversity emerge is a long-standing question in ecology. Theories and experimental studies suggested that community diversity and interspecific interactions are interdependent. However, evidence from multitaxonomic, high-diversity ecological communities is lacking because of practical challenges in characterizing speciose communities and their interactions. Here, I analyzed time-varying causal interaction networks that were reconstructed using 1197 species, DNA-based ecological time series taken from experimental rice plots and empirical dynamic modeling, and show that species interaction capacity, namely, the sum of interaction strength that a single species gives and receives, underpins community diversity. As community diversity increases, the number of interactions increases exponentially but the mean species interaction capacity of a community becomes saturated, weakening interaction among species. These patterns are explicitly modeled with simple mathematical equations, based on which I propose the "interaction capacity hypothesis", namely, that species interaction capacity and network connectance are proximate drivers of community diversity. Furthermore, I show that total DNA concentrations and temperature influence species interaction capacity and connectance nonlinearly, explaining a large proportion of diversity patterns observed in various systems. The interaction capacity hypothesis enables mechanistic explanations of community diversity, and how species interaction capacity is determined is a key question in ecology.