Galaxies in our Universe are not distributed randomly. Instead, they tend to group into clusters, following the gravitational potential generated by local enhancements in the density of the invisible dark matter. In this context, galaxy clusters are visible landmarks that signal the presence of dark matter overdensities; the abundance of the latter is directly controlled by a few fundamental parameters that we use to describe the composition and evolution of our Universe. Hence, by measuring the abundance of galaxy clusters, we can obtain indirect estimates on cosmological parameters. This project aims at developing an efficient and adaptable software program that, given as input the outcome of a cluster survey (the cluster number counts against their distance), is able to output corresponding best-fit estimates on these cosmological parameters. We plan to make the code public, as the starting point for novel, future results in cluster science.