To overcome these limitations, this work introduces a standalone, packageagnostic software designed to efficiently visualize the thermodynamic and kinetic properties of reaction networks, rNets. rNets is built on three core design principles: (i) ease of use for both programmers and non-programmers, (ii) readiness for integration with various DFT and microkinetic (MK) packages, and (iii) minimal dependency requirements to simplify deployment and enhance robustness. To demonstrate the capabilities of our code, we have integrated rNets with two distinct microkinetic modeling packages, showcasing its effectiveness in visualizing the complex reactions associated with both homogeneous and heterogeneous catalysts. Moreover, we have also coupled rNets with a knowledge-graph based representation of reaction networks, integrated within the ioChem-BD database for computational chemistry data. This approach not only streamlines the analysis of intricate catalytic networks but also bridges the gap between theoretical simulations and practical applications, offering a more comprehensive and accessible tool for researchers in the field of computational chemistry. Through rNets, we aim to facilitate a more rapid, automated and informed catalyst discovery process.