The most well-known large ligand database is the Kraken library that provides a massive amount (~300,000) of mostly hypothetical monodentate P III structures. This ligand database provides both structures as well as machine learning calculated properties and was developed based on the philosophy of representing the discrete ligands as continuous variables. As an important general demonstration of the utility of ligand libraries, Kraken has been used to predict cross-coupling reactions. A somewhat related virtual ligand-assisted screening procedure using phosphines was recently developed by Matsuoka and Maeda. To begin we developed a program (called Polyjuice) that can identify all ligands coordinated to a single metal center of a mononuclear structure. Briefly, Polyjuice first reads the connectivity throughout a metal-ligand structure and each molecule is considered as a graph data structure with all atoms as vertices and bonds between atoms as edges. A modified depth-first search algorithm was then used to identify and extract each ligand. Our modification of the depth-first search algorithm added a condition to handle polydentate ligands because the traversal will return to the metal through a different connecting atom.