Generative models have been successfully applied to de novo design, generating compounds which satisfy a wide variety of properties. The integration of QSAR models aim to incorporate structural information in the generative process. However, these models can suffer from limited applicability domains. Consequently, extrapolating out of sample can be unreliable and potentially misinform the generative agent especially when chemical space exploration is desired. We built upon recent work that incorporates molecular docking in place of QSAR models for better generalization. DockStream is presented as a molecular docking wrapper which provides access to a collection of ligand embedders and docking backends. The use of DockStream as a stand-alone docking tool was demonstrated by largescale docking efforts for a wide variety of targets and showcasing the automation of docking execution and post hoc analysis via the benchmarking and analysis workflow. The results show that it is beneficial to integrate several ligand embedders and docking backends in DockStream, so as to find a productive docking configuration for diverse end applications. The integration of DockStream with the recently published de novo design platform, REINVENT, demonstrates docking score optimization across all supported docking backends. The generated compounds retain vital interactions in the binding cavity and exploit new interactions. Extensive agreement with binding poses of known binders increases the confidence of the generated compounds and demonstrates the value of using docking to implicitly inform the generative process of 3D structural information. DockStream has the potential to be especially impactful in REINVENT experiments aiming at exploring novel chemotypes by providing a chemical space agnostic component that helps the agent learn to exploit the shape and intermolecular interactions of binding cavities.