Based on the user’s search prompt in the Jupyter Notebooks, media records of books, articles, and journals can be harvested and exported into versatile formats like Excel, JSON or CSV. This functionality empowers digital humanities researchers to efficiently manage metadata using familiar spreadsheet formats. The data is structured in a clear, cleaned and straightforward manner, facilitating easy filtering, sorting and calculation of search results within tables. The extracted metadata includes essential bibliographic fields like title, author, publisher, publication year, and location, paramount for reference generation. Additionally, derived fields, which were purposefully created in-house, such as epoch and resource type provide deeper context. Links to the table of contents allow for local bulk downloads of books’ table of contents in PDF format. Optional enrichment with Wikidata and GND reconciliation enhances insights derived from the amassed data.