Mass spectrometry imaging enables the spatially resolved analysis of molecular distributions in biological tissues. However, in situ untargeted metabolite identification remains challenging due to the inherent trade-off between spatial resolution and in situ tandem mass spectrometry (MS2) acquisition. Here, we developed clustering resampling mass spectrometry imaging (CR-MSI), a method that innovatively converts in situ MS2 acquisition from countless pixel scans to a few representative points testing. CR-MSI allows the acquisition of both spatial localization and structural fragmentation data for metabolites from a single tissue section. Additionally, we have engineered an integrated device that automates the CR-MSI workflow, transforming MS2 acquisition from an empirical, operator-dependent procedure to an objective, data-driven process. Moreover, the synchronization between MSI data acquisition and processing has improved the efficiency and overall MSI throughput. When applied to rat brain, CR-MSI collected 1,175 MS2 species, representing a 410% increase compared with conventional techniques. This approach will vastly enhance the structural elucidation of untargeted mass spectrometry imaging.