Computational methods and data science increasingly support optical microscopy experiments for biological investigations and medical applications. Increasingly complex methods and critical decision-making connected to biomedical studies require large and varied datasets for training, validation, and benchmarking. However, due to ethical constraints, sharing policies, and data variability, new studies struggle to access exhaustively large image collections. To address the limited dataset availability, we present the Optical Microscopy Simulator, an open-source repository for generating optical microscopy measurements by simulating samples and experimental degradations. To be adaptable to many experimental scenarios, samples are simulated as tuneable geometric shapes, such as round blobs, filaments, and connected structures, while experimental artifacts include simulations of blurring, different noise sources, uneven illumination, and other signal degradation effects due to sample bleaching or camera acquisition process. The repository enables users to create images from scratch or build on existing high-quality measurements. The software tool enables user-friendly, tuneable generation of samples and experimental artifacts, thus supporting the development of computational methods with simulations of full experimental processes, which can be generated by combining simple building blocks to create combinations of image degradation processes. The open-source Optical Microscopy Simulator includes functions, notebooks, and templates for immediate testing and straightforward integration in existing image data pipelines.