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Firecrawl Research is a purpose-built index for scientific and engineering research agents. It exposes a research-specific toolset for searching papers, inspecting paper metadata, reading relevant full-text passages, and discovering related papers through structural expansion. The index covers roughly 43 million paper abstracts. The majority of the corpus is biomedical and life sciences — PubMed, bioRxiv, and medRxiv — alongside arXiv for physics, mathematics, and computer science. Papers are addressable by their source ids, so pmid:, pmcid:, and doi: references work the same way arxiv: ones do.
  • Find papers by topic, method, benchmark, author, or category
  • Inspect canonical paper metadata and source ids
  • Read the passages in one paper that answer a specific question
  • Expand from strong seed papers to related papers, citers, or references
To give your agent access to the Research Index, we strongly recommend using our CLI or MCP, combined with our dedicated research skill, which you can install with:

How this relates to /search

From 2026-11-16, categories: ["research"] on /search searches this index and returns the same paper records in data.research. The table below describes its behavior until then. See search categories.
Firecrawl has two things named “research”, and they are not the same feature: Use the Research Index when you are doing literature work: finding papers, reading them, and following citations. Use categories: ["research"] when you want ordinary web pages that happen to live on academic domains.

Endpoints

The research index GitHub search was removed. GET /search/research/github and the legacy GET /research/github were removed on 2026-11-03. Both paths now return 410 Gone. Search GitHub issues, pull requests, and READMEs with the Developer Index instead.
Research Index calls are free and have a daily limit set by your plan, and Scale and Enterprise plans are unlimited. Searches, reads, inspects and related-paper lookups all count, including calls to the Research Index tool in Alexandria. See rate limits for the limit on each plan.

Search papers

Search paper abstracts with a natural-language query. The response returns ranked papers with canonical paperId, preferred primaryId, source ids, title, abstract, authors, creation and update dates, score, and optional ranking signals.
Optional filters:
  • authors: author substring filter; all filters must match
  • categories: paper category filter, such as cs.LG
  • from: inclusive created/updated lower bound, YYYY-MM-DD
  • to: inclusive created/updated upper bound, YYYY-MM-DD
  • sort: relevance (default) or date_desc, which returns the newest of the most relevant matches, newest first by created date. It does not list every paper in a date range; add from (and to) for that.

Biomedical example

Most of the index is life sciences, so clinical and molecular biology queries work the same way:
Results carry a primaryId in whichever namespace the source uses, so biomedical hits come back as pmid:<id>, pmcid:<id>, or doi:<doi>. Feed that value straight back into the inspect, read, and related endpoints below.

Inspect a paper

Use a canonical paperId or a source-specific primaryId. Accepted primaryId forms are arxiv:<id>, pmid:<id>, pmcid:<id>, and doi:<doi> — for example curl -s ".../v2/search/research/papers/pmid:<id>" for a PubMed record.

Read paper passages

Add query to the same paper path to retrieve the top full-text passages for a question. This is useful for verifying whether a candidate paper actually contains a method, dataset, constraint, or result before you include it.
Expand from one or more seed papers through semantic expansion and rank the candidates against a natural-language intent.
Modes:
  • similar: co-citation and bibliographic-coupling neighborhood
  • citers: papers that cite the seed
  • references: papers cited by the seed