The introduction of MassLite by Zhu et. al marks a notable advancement in the pretreatment of metabolomics data. This software package is an integrated Python platform with a user-friendly graphical interface for processing data in standard .mzML format. This tool is suitable to handle data from intermittent acquisition processes, enabling efficient segmentation of ion signals from individual cells. MassLite also retains low-intensity metabolite signals within complex single-cell data, broadening the scope of detectable molecular species from limited analyte content. Additionally, this tool incorporates functions for void scan filtering, dynamic grouping, and advanced background removal, all of which enhance data quality and processing efficiency. Further, MassLite automates cell region selection, replacing the manual process to enhance processing throughput. Overall, MassLite serves as a vital tool for advancing SCMS research, streamlining data preprocessing, and facilitating more accurate metabolomic analyses.