Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics may help to reveal the molecular basis of a disease, make a diagnosis, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lenses from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrating with other “-omics” data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing, with the final table containing information on the abundance of 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. The data were obtained using the bird specimens collected in compliance with ethical standards and revealed potential differences in metabolic pathways due to phylogenetic differences or environmental exposure.