This work presents the first investigation into Spontaneous Isolated Sign Language Recognition for Catalan Sign Language (LSC). Our work is grounded on the derivation of a dataset of signs and their glosses from a corpus of spontaneous dialogues and monologues. The recognition model is based on a Multi-Scale Graph Convolutional network fitted to our data. Results are promising since several signs are recognized with a high level of accuracy, and an average accuracy of 71% on the top 5 predicted classes from a total of 105 available. An interactive interface with experimental results is also presented. The data and software are made available to the research community.