CrossRef DOI & Citation Metadata Lookup

What is CrossRef DOI & Citation Metadata Lookup?

CrossRef DOI & Citation Metadata Lookup is an Apify Actor that resolves DOIs, DOI URLs or free-text citations and titles into structured bibliographic metadata — title, authors, journal, publisher, publication date, citation count, abstract, license and funder — and returns one clean row per item. Every lookup goes straight to the public CrossRef REST API (api.crossref.org): no scraping, no HTML parsing, no API key required. Paste a DOI such as 10.1038/nature12373, a https://doi.org/... link, or a plain-text citation like search:Attention is all you need, and the Actor finds the best CrossRef match for you.

Why use CrossRef DOI & Citation Metadata Lookup?

• Reference-list enrichment — turn a bibliography of raw DOIs or citation strings into a structured table with citation counts and abstracts, ready for a literature review.
• Research intelligence — track how often a paper is cited (citationCount), who funded it, and where it was published, for grant reporting or competitive research tracking.
• AI/RAG pipelines — feed an LLM agent verified metadata and abstracts for a list of papers instead of letting it hallucinate citation details.
• Publisher/journal analytics — resolve a batch of DOIs to compare journals, publishers, and licensing terms (open access URL vs. paywalled) at scale.

How to use CrossRef DOI & Citation Metadata Lookup

1. Paste your DOIs, DOI URLs, or citations into DOIs, DOI URLs or citations. Bare DOIs (10.1038/nature12373), full https://doi.org/... links, and plain titles all work; prefix ambiguous text with search: to force a bibliographic search.
2. Optionally enter your e-mail in Contact e-mail (polite pool) — CrossRef gives faster, more reliable service to requests that identify a contact.
3. Click Start. Each item becomes one dataset row; export it as JSON, CSV, Excel or HTML from the Output tab.

Example input

{
    "items": ["10.1038/nature12373", "https://doi.org/10.1145/3292500.3330919", "search:Attention is all you need"],
    "mailto": "you@example.com",
    "searchRows": 3,
    "maxConcurrency": 3
}

Example output

{
    "query": "10.1038/nature12373",
    "doi": "10.1038/nature12373",
    "doiUrl": "https://doi.org/10.1038/nature12373",
    "title": "Nanometre-scale thermometry in a living cell",
    "authors": ["G. Kucsko", "P. C. Maurer", "N. Y. Yao", "M. Kubo", "H. J. Noh", "P. K. Lo", "H. Park", "M. D. Lukin"],
    "authorCount": 8,
    "firstAuthor": "G. Kucsko",
    "journal": "Nature",
    "publisher": "Springer Science and Business Media LLC",
    "type": "journal-article",
    "publishedDate": "2013-07-31",
    "year": 2013,
    "volume": "500",
    "pages": "54-58",
    "citationCount": 1817,
    "referenceCount": 30,
    "licenseUrl": "http://www.springer.com/tdm",
    "matchScore": null,
    "error": null,
    "scrapedAt": "2026-09-12T18:00:00.000Z"
}

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Data table

Field	Type	Description
query	string	The input item exactly as given
doi, doiUrl	string	Normalised DOI and its https://doi.org/ permalink
title	string	Work title
authors, authorCount, firstAuthor, firstAuthorOrcid	array, number, string	Authors as "Given Family", count, first author and their ORCID
affiliations	array	Distinct author affiliation names
journal, publisher, type	string	Container title, publisher, and CrossRef work type
publishedDate, year	string, number	Earliest available publication date and year
volume, issue, pages	string	Journal volume, issue and page range
issn, isbn	array	ISSN(s) / ISBN(s) of the container
citationCount, referenceCount	number	Times cited (CrossRef-indexed) and number of references listed
abstract	string	Abstract with JATS XML tags stripped, capped at 3000 characters
licenseUrl, funders, subjects	string, array	License URL, funder names, subject tags
url, fullTextUrls	string, array	Canonical CrossRef URL and any publisher/TDM links
matchScore	number	CrossRef relevance score — present only for search: items
error, scrapedAt	string	Failure reason (if any) and lookup timestamp

Input parameters

Parameter	Type	Default	Description
items	array	["10.1038/nature12373"]	DOIs, DOI URLs, or citations/titles (prefix free text with search:)
mailto	string	""	Optional e-mail added to requests for CrossRef's "polite pool"
searchRows	integer	3	Candidate results CrossRef considers per free-text search (max 20)
maxConcurrency	integer	3	Items looked up in parallel (1-10)

Pricing

CrossRef DOI & Citation Metadata Lookup uses pay-per-event pricing: $0.001 per resolved item, i.e. $1 per 1,000 lookups, plus a negligible actor-start fee. Each item costs CrossRef exactly one HTTP request, so compute stays in the cents even for thousand-item batches. Set Maximum cost per run and the Actor trims the list to what the budget covers instead of overspending.

CrossRef DOI & Citation Metadata Lookup vs. manual DOI resolution

Looking up DOIs one at a time on doi.org or search.crossref.org means copy-pasting titles and citation counts by hand. This Actor takes a whole reference list — DOIs, links, or plain citations mixed together — and returns one structured dataset with authors, journal, citation count and abstract already parsed, ready to import into a spreadsheet, CRM, or research database. It also works from n8n, Make, Zapier and LangChain through Apify's integrations.

Using CrossRef DOI & Citation Metadata Lookup with AI agents and MCP

CrossRef DOI & Citation Metadata Lookup is pay-per-event with limited permissions — the two requirements for an Actor to be callable through the Apify MCP server at mcp.apify.com. An agent passes a list of DOIs or citation strings and gets back verified, structured metadata (not a hallucinated citation), ready to ground a literature summary, fact-check a reference, or build a reading list.

FAQ

What counts as a "DOI-shaped" item vs. a search? Anything containing a 10.xxxx/... pattern (bare, doi:-prefixed, or inside a doi.org URL) is resolved directly. Anything else — including text explicitly prefixed search: — is matched with CrossRef's bibliographic search, and the single best-scoring result becomes the row.

Why is abstract empty for some works? CrossRef abstracts are supplied by the publisher, and many publishers (especially older or non-open-access records) don't submit one. This is a CrossRef data gap, not an Actor error.

What is matchScore? CrossRef's relevance score for a search: match. It is null for direct DOI lookups, where there is nothing to score — the DOI is a unique key.

What are the limitations? CrossRef indexes metadata submitted by publishers; a very new DOI (registered in the last few hours) or an obscure publisher may not yet be indexed. A failing item still produces a row, with the reason in error.

Is this legal to run? Yes. CrossRef metadata is explicitly published for public reuse via a free, unauthenticated REST API, and no personal data is collected beyond publicly listed author names.

Can I export to CSV or Excel? Yes, from the Output tab or the API, with ready-made Overview and Full metadata views.

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Support and feedback

Found a citation style CrossRef mismatches, or a field you'd like added? Open an issue on the Issues tab.