To ensure a representative selection of MFI structures, we employed the furthest point sampling (FPS) algorithm to the datapoints obtained from molecular dynamics simulations of models with various water loadings (0, 1, 2, 3, and 17 water molecules per unit cell) and a Si/Al ratio of 95, all performed at a temperature of 350 K. FPS reduces the density of the initial point cloud by iteratively selecting points that are farthest from previously chosen ones -this ensures that the sampled structures are well-distributed across the dataset helping to data-efficiently cover a wide range of aluminium environments. As a result, the final database is characterized by structures covering a diverse range of water loading conditions, varying Si/Al ratios, and differing chemical compositions, including even some zeolites containing sodium atoms. Each aluminium atom within the selected structures serves as a datapoint, resulting in a set of over 4000 unique Al environments.