This work shows our pipeline for performing Mexican Sign Language recognition. We show the main steps of our process, which perform well when detecting letter signing (spelling). In particular, we propose to exploit alternative strategies for features of landmarks from the hand so that a simple MLP network can perform well. This approach will allow us to transport our model to a more extensive vocabulary and devices without heavy computing.