The molecular understanding of cellular processes requires the identification and characterization of the involved protein complexes. Affinity-purification and mass spectrometric analysis (AP-MS) are performed on a routine basis to detect proteins assembled in complexes. In particular, protein abundances obtained by quantitative mass spectrometry and direct protein contacts detected by crosslinking and mass spectrometry (XL-MS) provide complementary datasets for revealing the composition, topology and interactions of modules in a protein network. Here, we aim to combine quantitative and connectivity information by a webserver tool in order to infer protein complexes. In a first step, modeling protein abundances and functional annotations from Gene Ontology (GO) results in a network which, in a second step, is integrated with connectivity data from XL-MS analysis in order to complement and validate the protein complexes in the network. The output of our integrative approach is a quantitative protein interaction map which is supplemented with topological information of the detected protein complexes. compleXView is built up by two independent modules which are dedicated to the analysis of label-free AP-MS data and to the visualization of the detected complexes in a network together with crosslink-derived distance restraints. compleXView is available to all users without login requirements at http://xvis.genzentrum.lmu.de/compleXView.