Cities with strong local music scenes enjoy many social and economic benefits. To this end, we are interested in developing a locally-focused artist and event recommendation system called Localify.org that supports and promotes local music scenes. Local artists tend to be relatively obscure and reside in the long tail of the artist’s popularity distribution. In this demo paper, we describe both the overall system architecture as well as our core recommender system that uses artist-artist similarity information as opposed to user-artist preference information. We also discuss the role of popularity bias and how we attempt to ameliorate it in the context of local music recommendation.