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search_literature is the core Scite MCP tool. One tool covers three jobs: finding papers, reading inside them, and pulling the Smart Citation statements that cite them. Requires a Scite premium subscription.

What it returns

Every hit carries the paper’s identity plus the evidence attached to it. A type of unclassified means the citation statement exists but the classifier hasn’t assigned it a category. It isn’t a fourth citation category — see Citation model.

Three ways to call it

Search for papers

Pass term with domain-specific vocabulary. The index spans every academic field, so broad phrases return noise.

Fetch metadata for known papers

Pass dois (preferred) or titles without a term. No search runs; you get the records back.

Read inside a specific paper

Pass dois with a term. Each call returns up to 5 matching excerpts, so vary the term across calls to walk through a paper section by section.
If fulltextExcerpts comes back empty, the full text either isn’t indexed or your terms didn’t match. Use the access field to reach the PDF instead.

Query syntax

term searches across title, abstract, and full text, and supports:
  • Boolean operators: AND, OR, NOT
  • Phrase search: "exact phrase"
  • Proximity: "term1 term2"~5

Parameters

Calling search_literature with no arguments browses the whole corpus, relevance-sorted. That’s allowed but rarely useful — pass at least a term, dois, or titles.

Query and pagination

Keep limit small. Every hit can carry excerpts and citation statements, so large limits produce payloads that consume a lot of model context. Use 1050 with offset to page.

Metadata filters

Citation filters

Each filter is a range bound. tally counts citation statements; citingPublications counts distinct publications.
The API field is contrasting, matching the parameter names above. Scite’s interface labels the same category “contrasted.” Both refer to contradicting citation statements.

Editorial filters

Check editorialNotices on every paper before citing it, even when you haven’t filtered on these. A paper can be accurate and still be withdrawn.

Reading a paper efficiently

The token-efficient pattern is search once, then read incrementally.
1

Find the paper

Search with a narrow term and a small limit to get candidate DOIs.
2

Confirm it

Call again with dois and no term to pull metadata, tally, and editorialNotices.
3

Read sections

Call repeatedly with the same dois and different term values — methods, results, limitations — collecting 5 excerpts per call.
4

Follow the citations

Read the citations array for what other papers say about it, quoting snippet text as evidence.