Crossref DOI Metadata Scraper
Pricing
from $7.00 / 1,000 results
Crossref DOI Metadata Scraper
Scrapes Crossref publication metadata by search query, title, author, or specific DOI. Returns each work as a flat row with title, authors, container, publication date, and DOI.
Pricing
from $7.00 / 1,000 results
Rating
5.0
(1)
Developer
ParseForge
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7
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2 days ago
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Crossref DOI Metadata Scraper
Scrape Crossref DOI metadata for any publication, search query, or single DOI, up to a million works per run. Every record comes with its title, authors, container, publication date, and DOI. No API key. Export to CSV, JSON, Excel, or XML.
Crossref's official API is free but rate-limited and returns deeply nested JSON that is painful to flatten. This Actor queries the public REST API directly, applies your filters as it reads, and returns each matching work as one flat row. Search by title, author, free text, or a specific DOI, and collect up to a million records per run.
| Who uses it | What they scrape Crossref for |
|---|---|
| Academic researchers | Building a literature review dataset for a specific topic |
| Librarians | Enriching a catalog with complete DOI metadata |
| Data analysts | Tracking publication output by author or institution |
| Journal editors | Monitoring citations and metadata for their journal |
What it does
This Actor collects Crossref publication metadata by search query, title, author, or specific DOI, and returns each work as a flat row.
- ๐ Search by free text: query across titles, authors, container titles, and more.
- ๐ Filter by title or author: narrow results to exact title or author name matches.
- ๐ฏ Fetch a single DOI: retrieve complete metadata for one known DOI, overriding any query.
- โ๏ธ Crossref filter string: pass raw filter parameters like type, from-pub-date, or has-orcid.
- ๐ง Polite pool email: provide a contact email to get faster, more reliable responses from Crossref.
Results export to CSV, JSON, Excel, or XML, or straight from the API.
What you can do with Crossref data
๐ Build a literature review dataset.
A PhD student searches for 'attention is all you need' and collects 500 matching works with titles, authors, and publication dates to seed their bibliography.
๐ Enrich a catalog with DOI metadata.
A librarian runs the Actor with a list of DOIs to fill missing title, author, and container fields in their institutional repository.
๐ Track an author's publication output.
A research analyst queries by author name and filters by from-pub-date to compile a yearly publication list for a faculty review.
๐ Monitor journal citations.
A journal editor uses the filter string 'type:journal-article,container-title:Nature' to collect recent articles and analyze citation patterns.
Why choose this scraper
| What you get | |
|---|---|
| No API key | Uses Crossref's public REST API, no registration required |
| Flat output | Nested JSON is flattened into one row per work |
| Up to 1M records | Collect up to a million works per run |
| Polite pool | Optional email puts you in Crossref's faster queue |
How it compares
No other Store actor targets Crossref the same way, so the honest comparison is with the alternatives teams actually weigh.
| Crossref DOI Metadata Scraper | Build it in-house | By hand | |
|---|---|---|---|
| Setup | Run it now, zero config | Days of engineering | None, but hours per pull |
| When Crossref changes | Maintained for you | You fix it | You re-learn the page |
| Proxies, retries, anti-bot | Built in | Your problem | Browser only |
| Output | Fixed JSON schema, CSV/Excel export | Whatever you build | Copy-paste |
| Cost | Pay per result | Engineering time | Analyst hours |
Configure the run
Drive the Actor from a free text query, a title, an author name, or a specific DOI, and filters run as each work is read so only matches reach your dataset. The Input tab lists every parameter.
A first run with the defaults:
{"maxItems": 10,"query": "attention is all you need"}
A larger pull:
{"maxItems": 200,"query": "attention is all you need"}
Pricing
Pay-per-result: $0.08 per result collected. You pay only for the results written to your dataset.
| Results collected | Approximate cost |
|---|---|
| 100 results | $8.00 |
| 1,000 results | $80.00 |
| 10,000 results | $800.00 |
New Apify accounts start with $5 in free credit.
Free users
Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.
Run it
- Create a free Apify account with $5 in credit.
- Open the Crossref DOI Metadata Scraper.
- Set your inputs and any filters, then click Start.
- Export the results as CSV, Excel, JSON, or XML from the Dataset tab.
Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.
Use with AI agents (MCP)
Give an AI agent live access to Crossref through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:
$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/crossref-scraper"
Then prompt it in plain language to run the scraper and read back the results.
Troubleshooting
Why am I getting no results?
Check your query for typos or overly restrictive filters. Try a broader search term or remove the filter string. Also ensure you are not using a specific DOI that does not exist.
Why is the run slow?
Crossref rate limits apply. Provide an email in the input to join the polite pool, which allows faster request rates. Reduce maxItems if you only need a sample.
Why are some fields empty in the output?
Not all Crossref records have every field. For example, some works may lack an abstract or ORCID. Empty fields are normal for incomplete metadata.
Why did the run stop before reaching maxItems?
Crossref may have no more results for your query. Try a different search term or remove filters to see if more records are available.
FAQ
| Question | Answer |
|---|---|
| Do I need a Crossref API key? | No. This Actor uses Crossref's public REST API, which does not require an API key. Providing an email in the input puts your requests in the polite pool for faster responses. |
| How many records can I collect per run? | You can set maxItems up to 1,000,000. The Actor will stop after collecting that many works or when Crossref has no more results for your query. |
| Can I fetch metadata for a single DOI? | Yes. Enter the DOI in the 'Specific DOI' field and the Actor will return that one work, ignoring any other query parameters. |
| What is the filter string? | It is a raw Crossref filter parameter, such as 'type:journal-article,from-pub-date:2024,has-orcid:true'. You can find the full syntax in the Crossref API documentation. |
| Does the Actor flatten nested metadata? | Yes. Crossref returns deeply nested JSON, but this Actor flattens each work into a single row with fields like title, authors, container title, and publication date. |
| Can I search by author name? | Yes. Use the 'Author name' field to match works by a specific author. You can combine it with other filters. |
| What export formats are supported? | You can export the dataset to CSV, JSON, Excel, or XML from the Apify platform. |
| Is there a rate limit? | Crossref has rate limits on its public API. Providing an email in the polite pool increases your allowed request rate. |
| Can I filter by publication date? | Yes. Use the filter string with 'from-pub-date' or 'until-pub-date' parameters, or include them in your free text query. |
| Does this Actor work with any Crossref content type? | Yes. It returns journal articles, conference papers, books, datasets, and other works indexed by Crossref. |
Related actors
Browse the full ParseForge collection for more scrapers.
๐ Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.
โ ๏ธ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Crossref. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.
