We study the supercluster shape properties of the recently compiled Sloan Digital Sky Survey (SDSS) cluster catalogue using an approach based on differential geometry. We detect superclusters by applying the percolation algorithm to observed cluster populations, extended out to z_max_<=0.23 in order to avoid selection biases. We utilize a set of shapefinders in order to study the morphological features of superclusters with >=8 cluster members and find that filamentary morphology is the dominant supercluster shape feature, in agreement with previous studies.