Metal-organic frameworks (MOFs) stand as versatile porous materials with exquisitely tunable structures, and tremendous potential for numerous applications across various fields. A large fraction of these applications seek to exploit the adsorption properties of these materials, which are composed of interconnected building blocks (i.e., metallic nodes and organic linkers). For instance, numerous MOFs could be imparted with adsorption properties to substitute ca. 80% of heat-based chemical separations processes with adsorption-based ones. Therefore, harnessing the full potential of MOFs, and accelerating their development by anticipating MOF designs that embody desired properties through computation requires reliable predictions of adsorption behavior within these intricate frameworks.