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Human leukocyte antigen (HLA)-bound tumor peptides can be routinely isolated from cancer samples and identified using mass spectrometry (MS). However, MS approaches can be stochastic or rely on spectral libraries, which are not customarily available for individual-specific peptides, thus limiting the ability to discover novel peptides. Here, we introduce Pepyrus, which generates user-defined, individual-specific or disease-specific peptide libraries in Escherichia coli to improve the sensitivity and confidence of MS peptide identification, including lowly abundant neoantigens. Using Pepyrus-generated peptide libraries paired with an HLA-specific data-independent acquisition strategy, we recover >75% of the expected sequences per single injection for libraries of >10,000 peptides and identify 0.1 fmol of spiked-in peptides in a complex background. We apply Pepyrus to create personalized libraries, facilitating identification of clinically relevant HLA peptides, including several novel peptides from cell lines derived from persons with melanoma and renal cell carcinoma. Pepyrus enables identification of rare HLA-bound peptides and provides the ability to generate large training datasets to improve spectra, retention time and ion mobility prediction tools.