It is becoming increasingly common for laboratories and universities to share computing resources. Also as cloud usage and applications continue to expand, a hybrid cloud working model is fast becoming a common standard practice. In line with these present-day trends, we present in this paper an open-source Python library that provides information on high performance computing (HPC) clusters and systems that are available to a user via a peer to peer (P2P) infrastructure. These metrics include the size of system and availability of nodes, along with the speed of connection between clusters. We will present the benefits of using a P2P model compared to traditional client server models and look at the ease in which this can be implemented. We will also look at the benefits and uses of gathering this data in one location in order to assist with the managing of complex workloads in heterogeneous environments.