Abstract Fluorescent in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotide (oligo)-based FISH methods. These methods have enabled researchers to study the three-dimensional organization of the genome at super-resolution and visualize the spatial patterns of gene expression for thousands of genes in individual cells. While considerable progress has been made in developing new molecular methods that harness complex oligo libraries for FISH, there are few existing computational tools to support the bioinformatics workflows necessary to carry out these experiments. Here, we introduce Paint Server and Homology Optimization Pipeline (PaintSHOP), an interactive platform for the reproducible design of oligo FISH experiments. PaintSHOP enables researchers to identify probes for their experimental targets efficiently, to incorporate additional necessary sequences such as primer pairs, and to easily generate standardized files documenting the design of their libraries. Our platform integrates a machine learning model that quantitatively predicts probe specificity on the genome scale into a dynamic web application that creates ready-to-order probe sets for a wide variety of applications. The goal of this freely available web resource is to democratize and standardize the process of designing complex probe sets for the oligo FISH community. PaintSHOP can be accessed at: paintshop.io