Solid-state nuclear magnetic resonance (NMR) is capable of providing extremely detailed insights into the structure and dynamics of a wide range of materials - from organic systems, such as pharmaceutical compounds and supramolecular arrays, to inorganic materials for next-generation batteries and safe storage of nuclear waste. Such information is crucial for harnessing the properties of increasingly complex new materials, and to address major challenges across the physical sciences. However, the true potential of this experimental technique is only realized through combination with advanced computational methods. In particular, first-principles electronic structure predictions of key NMR interactions, such as chemical shifts, allow experimental measurements to be directly linked to structure. In tackling challenging problems, the developing field of NMR crystallography benefits from close interaction with other experimental techniques, typically powder X-ray diffraction, and computational approaches, particularly crystal structure prediction. The Collaborative Computational Project for NMR Crystallography supports this multidisciplinary community of NMR spectroscopists, crystallographers, materials modellers and application scientists, who work both within academia and industry. We develop overarching software tools enabling a largely experimentally focused community to exploit advanced computational techniques.