Single cell proteomics (SCP) is rapidly emerging and can quantify > 1000 proteins per cell. Significant advances in instrumentation and sample preparation are making SCP more broadly accessible. Yet technical advances in data acquisition have not been paired with advances to computational tools. Algorithms for proteomics were designed and optimized on data from bulk proteomics, and are ill-suited for SCP data. Our preliminary research shows that data from SCP lack many features that are critical for current proteomics algorithms. We will dramatically improve accuracy and coverage of the single cell proteome through creation of the first-ever dedicated SCP search software. This will be coupled with an initiative to improve SCP peptide and protein quantification. These algorithmic improvements will be informed from a large corpus of SCP data, gathered and centralized into the first SCP data archive.