Tandem mass tag (TMT)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a proven approach for large-scale multiplexed protein quantification. However, the identification of TMT-labeled peptides is compromised by the labeling during traditional sequence database searches. In this study, we aim to use a spectral library search to increase the sensitivity and specificity of peptide identification for TMT-based MS data. Compared to MS/MS spectra of unlabeled peptides, the spectra of TMT-labeled counterparts usually display intensified b ions, suggesting that TMT labeling can alter product ion patterns during MS/MS fragementation. We compiled a human TMT spectral library of 401,168 unique peptides of high quality from millions of peptide-spectrum matches in tens of profiling projects, matching to 14,048 nonredundant proteins (13,953 genes). A mouse TMT spectral library of similar size was also constructed. The libraries were subsequently appended with decoy spectra to evaluate the false discovery rate, which was validated by a simulated null TMT data set. The performance of the library search was further optimized by removing TMT reporter ions and selecting an appropriate library construction method. Finally, we searched a human TMT data set against the spectral library to demonstrate that the spectral library outperformed the sequence database. Both human and mouse TMT libraries were made publicly available to the research community.