Sport climbing has become a popular sport, and every year new climbing areas (crags) with climbing routes around the world are developed. This increased amount of outdoor crags leads to the problem when climbers have to spend a lot of time trying to understand which climbing crag they would like to visit and which climbing route to climb. Unfortunately, nowadays, there is no IT solution for automatically supporting climbers to choose climbing crags or routes based on their preferences, thus, we aim to address this issue by building a content-based climbing recommender system developed for Arco, Italy. The preferences of the users are learned via explicit feedback given through the mobile climbing application, which is mainly used by the climbing community as an electronic climbing guidebook and logbook to record their training information. The initial usability study showed that the system achieves high interest among climbers. Furthermore, the developed prototype of the climbing recommender system would be presented. At the end of the talk, we show the integration of image-based recommender technologies for improving content-based recommendations.