Micha and Viki are happy to announce that the manuscript for the updated version of our cross-linking search engine MS Annika 2.0 has been published in the Journal of Proteome Research (https://doi.org/10.1021/acs.jproteome.3c00325). MS Annika 2.0 implements a new search algorithm that, in addition to MS2 level only, supports the processing of data from MS2−MS3-based approaches for the identification of peptides from MS3 spectra and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika 2.0 detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. MS Annika 2.0 is available via https://ms.imp.ac.at/?action=ms-annika or https://github.com/hgb-bin-proteomics/MSAnnika.