Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerful tool for studying the mechanical properties, intermolecular and intramolecular interactions, unfolding pathways, and energy landscapes of membrane proteins. One limiting factor for the large-scale applicability of SMFS on membrane proteins is its low efficiency in data acquisition. We have developed a semi-automated high-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, we present a coarse filter to efficiently extract protein unfolding events from large data sets. The HT-SMFS procedure and the coarse filter were validated using the proton pump bacteriorhodopsin (BR) from Halobacterium salinarum and the L-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen for molecular interactions between AdiC and its substrates, we recorded data sets in the absence and in the presence of L-arginine, D-arginine, and agmatine. Altogether ∼400 000 force-distance curves were recorded. Application of coarse filtering to this wealth of data yielded six data sets with ∼200 (AdiC) and ∼400 (BR) force-distance spectra in each. Importantly, the raw data for most of these data sets were acquired in one to two days, opening new perspectives for HT-SMFS applications.