  Galaxy clusters enable unique opportunities to study cosmology, dark matter,
galaxy evolution, and strongly-lensed transients. We here present a new
cluster-finding algorithm, CluMPR (Clusters from Masses and Photometric
Redshifts), that exploits photometric redshifts (photo-z's) as well as
photometric stellar mass measurements. CluMPR uses a 2-dimensional binary
search tree to search for overdensities of massive galaxies with similar
redshifts on the sky and then probabilistically assigns cluster membership by
accounting for photo-z uncertainties. We leverage the deep DESI Legacy Survey
grzW1W2 imaging over one-third of the sky to create a catalogue of ~ 300,000
galaxy cluster candidates out to z = 1, including tabulations of member
galaxies and estimates of each cluster's total stellar mass. Compared to other
methods, CluMPR is particularly effective at identifying clusters at the high
end of the redshift range considered (z = 0.75-1), with minimal contamination
from low-mass groups. These characteristics make it ideal for identifying
strongly lensed high-redshift supernovae and quasars that are powerful probes
of cosmology, dark matter, and stellar astrophysics. As an example application
of this cluster catalogue, we present a catalogue of candidate wide-angle
strongly-lensed quasars in Appendix C. The five best candidates identified from
this sample include two known lensed quasar systems and a possible
changing-look lensed QSO with SDSS spectroscopy. All code and catalogues
produced in this work are publicly available (see Data Availability).
