Multi-API Literature Query Tool

Search the scientific literature across multiple academic APIs in one workflow

The Multi-API Literature Query (MALQ) Tool solves this by letting you search multiple academic databases in a single workflow, combining broad coverage with reproducible search strategies. I built it for myself because it made it easy to catch relevant papers in one reproducible workflow. That personal need turned into a tool that I hope would help if you are doing broad or interdisciplinary literature discovery.


What It Does

MALQ sends coordinated literature searches across several major scholarly APIs at once, including:

  • PubMed
  • Europe PMC
  • Semantic Scholar
  • OpenAlex
  • Crossref
  • CORE
  • arXiv

Why It’s Useful

MALQ improves recall, breadth, and reproducibility by making it easy to search across multiple ecosystems in parallel.

  • literature reviews
  • grant writing
  • project scoping
  • finding datasets and benchmark papers
  • interdisciplinary discovery
  • systematic and semi-systematic reviews
  • building paper corpora for downstream NLP or RAG pipelines

A Note on Limitations

MALQ is designed to cast a much wider net than searching a single database, but no automated literature search can guarantee perfect coverage.

Results vary depending on the wording of the query, API availability, provider-side ranking behavior, and rate limits. Some APIs also require keys for higher throughput or more reliable batching, while others may occasionally return incomplete metadata.

In practice, I treat it as a high-recall first pass: a way to catch as much relevant work as possible early, then refine the search strategy based on what the first round reveals.


Open Source

MALQ is open source and designed for practical use in real research workflows.

Code: GitHub

Whether you’re preparing a systematic review, exploring a new topic, or building a paper corpus for machine learning, MALQ makes literature discovery faster, broader, and easier to reproduce.

Citation

If you use this code in your research, please cite:

DOI: 10.5281/zenodo.19389717