Metal-Organic Frameworks (MOFs) are highly versatile materials owing to their vast structural and chemical tunability. These hybrid inorganic-organic crystalline materials offer an ideal platform to incorporate light-harvesting and catalytic centers and thus, exhibit a great potential to be exploited in solar-driven photocatalytic processes such as H2 production and CO2 reduction. To be photocatalytically active, UV-visible optical absorption and appropriate band alignment with respect to the target redox potential is required. Despite fulfilling these criteria, the photocatalytic performance of MOFs is still limited by their ability to produce long-lived electron-hole pairs and long-range charge transport. In this work, we present a computational strategy to address these two descriptors in MOF structures and translate them into charge transfer numbers and effective mass values. We apply our approach to 15 MOF structures from the literature that encompass the main strategies used in the design of efficient photocatalysts including different metals, ligands, and topologies. Our results capture the main characteristics previously reported for these MOFs and enable us to identify promising candidates. In the quest of novel photocatalytic systems, high-throughput screening based on charge separation and charge mobility features is envisioned to be applied in large databases of both experimentally and in silico generated MOFs.