/firecrawl-research-index

name: firecrawl-research-index
description: Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

Firecrawl Research Index

Find the research papers that answer a research query. Some questions have a single answer; many have several — and when in doubt, lean toward returning the fuller relevant set (most relevant first) rather than narrowing to one. A reader is better served seeing the neighboring methods and papers than having them silently dropped.

What is in the index

Paper abstracts, with full text reachable per paper. The largest share of the corpus is **biomedical and life-science** literature — **PubMed** journal articles plus **bioRxiv** and **medRxiv** preprints — so clinical, drug, gene, disease, epidemiology, and public-health questions are in scope. **arXiv** preprints cover computer science, physics, and mathematics. Coverage outside those sources is thinner: a paper that exists only behind a publisher paywall or in a niche venue may not be indexed, and the general web tools below are the fallback when it isn't.

There is **no fixed recipe**. Read the query, decide what kind it is, and choose the approach below. Some queries need a single search; others need heavy structural/semantic expansion. Don't run machinery a query doesn't call for.

The tools, and what each is uniquely good at

• MCP: **`firecrawl_research_search_papers(query, k?)`**

CLI: **`firecrawl research search-papers <query> [--k <number>]`** Semantic (HyDE) search over **abstracts**. The natural first move for almost any query. If results look thin or all-alike, re-run with a different framing (sibling domain, rival method, dataset/benchmark name) rather than giving up.

• MCP: **`firecrawl_research_related_papers(seed_ids, intent, mode?, k?)`**

CLI: **`firecrawl research related-papers <seedIds...> --intent <intent> [--mode <similar|citers|references>] [--k <number>]`** Semantic and structural expansion, ranked to your `intent`. This reaches papers semantic search _cannot_, and it's how you turn one good hit into the rest of a set. `mode=similar` → niche siblings; `citers` → who uses/builds on the seeds; `references` → what they build on / compare against.

• MCP: **`firecrawl_research_inspect_paper(id)`**

CLI: **`firecrawl research inspect-paper <id>`** Canonical metadata for **one** paper: title, abstract, authors, categories, source ids, and dates. Use it after `search_papers` or `related_papers` when you need the complete citation/metadata for a candidate, or when you have an id from elsewhere and need to confirm what paper it resolves to. This does **not** read the paper body; use `read_paper` for specific full-text questions.

• MCP: **`firecrawl_research_read_paper(id, question)`**

CLI: **`firecrawl research read-paper <id> --question <question>`** In-body passages of **one** paper, to verify a load-bearing constraint (a method actually used, a score actually reported, an affiliation, what a paper compares to). Use it to settle a specific doubt, not on everything.

• MCP: **`firecrawl_search(query, categories: ["research"])`**

CLI: **`firecrawl search <query> --categories research`** **Not this index.** This is a _website_ filter: it restricts a normal web search to a short list of research-affiliated domains — the list does include `pubmed.ncbi.nlm.nih.gov`, `biorxiv.org`, `medrxiv.org`, and `arxiv.org` alongside publisher sites — and returns page results in a `research` group beside `web`, each with `url`, `title`, `description` (the matched passage), `position`, and `category: "research"` — web results carry no `category`, so that is the field to key on when merging. So it reaches those sites' **web pages**; what it does not do is query their **paper records** in this index — no semantic search over abstracts, no citation-graph or related-paper expansion, no canonical paper metadata, and no in-body passages. The results are ordinary web results. Use it when you are **already** running a web search and want those sites weighed in the same call. For anything that is actually a paper-finding task, use `firecrawl_research_search_papers` and its siblings above.

• MCP: **`firecrawl_search(query)` / `firecrawl_scrape(url)`**

CLI: **`firecrawl search <query>` / `firecrawl scrape <url>`** General **web** search and page fetch, for facts that don't live in paper abstracts: benchmark **leaderboards**, rankings, "who scores best / is largest / is most used." Find the ranking on the web, then map the top entries back to papers with `search_papers`. Reach for these only when the corpus can't answer the question on its own.

Match the approach to the query

• **Single _named_ paper** ("the Qwen3 report") → one `search_papers`, done. This is the only case that truly wants exactly one paper.
• **Paper by description / by method or technique** ("the paper that introduced X", "training-free N-gram detection of AI text") → find the best match, then assume there's a _family_: expand with `related_papers` and **include