In conclusion, we have developed an automated low-cost workflow for rapidly screening the self-assembly landscape and host:guest behavior of MOCs. The use of an automated platform for screening the assembly outcomes enables the parallelization of MOC synthesis, made possible due to the reduced volume of reactants, specifically ligand, required per reaction, and the decreased human resource required in the preparation and analysis of the samples. Automation of data analysis through a free, simple, open-source workflow created a method to rapidly assign HRMS and interpret 1 H NMR spectra to determine the reaction outcome, which was based on a combined assessment of the reactivity by conversion and identification of the topological species, reducing experimental cost and effort. On rapid filtering of the results, identification and scale-up of hits was then carried out. One could argue that a limitation of our workflow is that analysis was conducted on crude reaction mixtures without any purification steps, but it should be noted that self-assembly reactions are often analyzed as crude mixtures before attempts at isolation are carried out to identify the equilibrium product, which could be perturbed on work-up. However, due to the trade-off between the information gained and the lack of multiple additional, expensive steps to achieve purification in an automated manner, this level of analysis was deemed acceptable.