Interactive notebooks allow people to communicate and collaborate through a single rich document that might include live code, multimedia, computed results, and documentation, which is persisted as a whole for reproducibility. Notebooks are currently being used extensively in domains such as data science, data journalism, and machine learning. Constructing a notebook interface for a new language, however, requires a lot of effort. In this paper, we present Bacatá, a language parametric notebook generator for domain-specific languages (DSL) based on the Jupyter framework. Bacatá is designed so that language engineers may reuse existing language components (such as parsers, code generators, interpreters, etc.) as much as possible. We present the design of Bacatá and how DSL notebooks can be generated with minimum effort in the context of the Rascal metaprogramming system and language workbench. We demonstrate Bacatá’s utility by generating notebook interfaces for three languages, Halide* (a DSL for image processing), SweeterJS (an extended version of Javascript), and QL (a DSL for questionnaires). Our results show that notebooks generated by Bacatá often only require a few lines of code to wire existing components together.