The increasing popularity of high-resolution mass spectrometry has led to many custom software solutions to process, interpret, and reveal information from high-resolution mass spectra. Although there are numerous software packages for peak-picking, calibration, and formula-finding, there are additional layers of information available when it comes to detecting repeated motifs from polymers or molecules with repeating structures or products of chemical or biochemical transformations that exhibit systematic, serial chemical changes of mass. Constellation is an open-source, Python-based web application that allows the user first to expand their high-resolution mass data into the mass defect space, after which a trend finding algorithm is used for supervised or unsupervised detection of repeating motifs. Many adjustable parameters allow the user to tailor their trend-search to target particular chemical moieties or repeating units, or search for all potential motifs within certain limits. The algorithm has a built-in optimization routine to provide a good starting point for the main trend finding parameters before user customization. Visualization tools allow interrogation of the data and any trends/patterns to a highly specific degree and save publication-quality images directly from the interface. As Constellation is deployed as a web application, it is easily used by anyone with a web browser; no software download or high-powered computer is required, as computations are performed on a remote high-powered data server run by our group.