Research Papers Scraper: search 250M+ scholarly works from OpenAlex

Get research papers as clean, structured records: title, DOI, abstract, authors with ORCIDs and institutions, venue, topics, citation counts and open-access PDF links. This research papers scraper reads the official, open OpenAlex API, the free catalog of the world's research (more than 250 million works, CC0-licensed). Search by keyword, look up DOIs, pull an author's or a university's publications, or walk a paper's citation network. No browser, no login, no blocking. $0.50 per 1,000 records.

We do not scrape Google Scholar. OpenAlex is an open data source built for automated use, so results are stable and the data can be reused freely.

What can this research papers scraper do?

• Search papers by keywords in the title and abstract, the title only, or the full text, with AND, OR, NOT and "exact phrases".
• Filter by publication year range, open access only, work type (article, review, preprint, book, dataset, dissertation...), OpenAlex topics (enter a name like CRISPR or an ID like T10878), minimum citations, language, abstract present, and exclude retracted papers.
• Sort by relevance, most cited, newest or oldest.
• Get papers by ID: DOIs, OpenAlex work IDs or PubMed IDs, looked up in batches of 50.
• Authors + their papers: names, ORCIDs or OpenAlex author IDs. You get the author profile (works count, citations, h-index, i10-index, last known institutions, main topics) followed by their papers.
• Institutions + their papers: names, ROR IDs or OpenAlex institution IDs. You get the institution profile (country, city, type, homepage, works, citations, h-index) followed by its papers.
• Citation expansion: for seed papers, get the papers that cite them (cited by), the papers they cite (references), or both.
• Large result sets: pages through results automatically, 100 per request, with cursor paging when you supply an OpenAlex API key.

What data do you get?

Every paper record has: openAlexId, title, doi, doiUrl, publicationYear, publicationDate, type, language, venue (journal, repository or conference), venueType, issn, publisher, volume, issue, pages, authorNames, firstAuthor, authorsCount, authors (each with name, orcid, openAlexId, position, isCorresponding, institutions, countries), institutions, abstract (rebuilt from OpenAlex's inverted index into plain text), primaryTopic, subfield, field, domain, topics, keywords, citedByCount, referencesCount, fwci (field-weighted citation impact), isOpenAccess, oaStatus, oaUrl, pdfUrl, landingPageUrl, license, isRetracted, pmid, openAlexUrl and apiUrl. Optional: referencedWorks (IDs of every paper it cites).

Records also say where they came from: query (search), input (ID lookups), seedType, seedId, seedName (author or institution), or relation (seed, citing, referenced) and seedTitle (citations).

Author and institution profiles have recordType set to author or institution, so you can filter them out of a paper list.

Who uses it?

• Researchers and students building literature reviews, reading lists and systematic-review screening sets.
• Research offices and libraries tracking their institution's output, open-access share and citations.
• R&D, pharma and biotech teams monitoring new publications on a target, method or competitor lab.
• Grant, funding and policy analysts measuring research activity by topic, country or institution.
• AI and data teams collecting abstracts and metadata for RAG systems, classifiers and knowledge graphs.
• Recruiters and business developers finding active experts in a field through their recent papers (public academic profiles only).

How to use it

1. Click Try for free (or Start). With no changes it returns the 50 most relevant papers for "large language models" in a few seconds.
2. Choose What to get: search papers, get papers by ID, authors, institutions or citations.
3. Enter your query, IDs, author names or institutions, and set any filters (years, open access, type, topics, minimum citations, sort).
4. Set Maximum results and run it.
5. Download the results as Excel, CSV, JSON or HTML, or schedule the run to watch for new papers.

Input example

{
  "mode": "searchWorks",
  "query": "large language models",
  "searchIn": "titleAbstract",
  "yearFrom": 2023,
  "openAccessOnly": true,
  "workTypes": ["article", "review"],
  "minCitations": 20,
  "sortBy": "citations",
  "maxResults": 500
}

More examples:

• Papers by DOI: {"mode": "getWorks", "workIds": ["10.1038/nature14539", "W2741809807", "26771483"]}
• Author and their most cited papers: {"mode": "authors", "authors": ["0000-0001-9161-999X", "Geoffrey Hinton"], "maxWorksPerSeed": 100, "sortBy": "citations"}
• A university's open-access papers since 2024: {"mode": "institutions", "institutions": ["https://ror.org/042nb2s44"], "yearFrom": 2024, "openAccessOnly": true, "maxWorksPerSeed": 1000}
• Who cites a paper: {"mode": "citations", "workIds": ["10.1038/nature14539"], "citationDirection": "citedBy", "maxWorksPerSeed": 1000, "sortBy": "newest"}

Output example

From a real default run (abstract and lists shortened here):

{
  "recordType": "work",
  "openAlexId": "W4362515116",
  "title": "A Survey of Large Language Models",
  "doi": "10.1007/s11704-026-60308-3",
  "doiUrl": "https://doi.org/10.1007/s11704-026-60308-3",
  "publicationYear": 2026,
  "publicationDate": "2026-05-09",
  "type": "article",
  "language": "en",
  "venue": "Frontiers of Computer Science",
  "venueType": "journal",
  "issn": "2095-2228",
  "publisher": "Higher Education Press",
  "volume": "20",
  "issue": "12",
  "firstAuthor": "Wayne Xin Zhao",
  "authorsCount": 23,
  "authors": [
    {
      "name": "Wayne Xin Zhao",
      "orcid": "0000-0002-8333-6196",
      "openAlexId": "A5037145565",
      "position": "first",
      "isCorresponding": false,
      "institutions": ["Renmin University of China"],
      "countries": ["CN"]
    }
  ],
  "institutions": ["Renmin University of China", "Université de Montréal"],
  "abstract": "The rapid evolution of large language models (LLMs) has driven a transformative shift in artificial intelligence (AI), reshaping both research paradigms and practical applications...",
  "primaryTopic": "Topic Modeling",
  "subfield": "Artificial Intelligence",
  "field": "Computer Science",
  "domain": "Physical Sciences",
  "topics": ["Topic Modeling", "Natural Language Processing Techniques", "Multimodal Machine Learning Applications"],
  "keywords": ["large language models", "pre-training", "self-supervised learning", "model architecture"],
  "citedByCount": 2093,
  "isOpenAccess": true,
  "oaStatus": "hybrid",
  "oaUrl": "https://link.springer.com/content/pdf/10.1007/s11704-026-60308-3.pdf",
  "pdfUrl": "https://link.springer.com/content/pdf/10.1007/s11704-026-60308-3.pdf",
  "landingPageUrl": "https://doi.org/10.1007/s11704-026-60308-3",
  "license": "cc-by",
  "isRetracted": false,
  "openAlexUrl": "https://openalex.org/W4362515116",
  "query": "large language models"
}

How much does it cost?

$0.50 per 1,000 records ($0.0005 each), plus a $0.00005 start fee per run. A record is one paper, author profile or institution profile.

You get	You pay
The default search (50 papers)	about $0.03
A 1,000-paper literature search	$0.50
An author profile plus their 500 papers	about $0.25
100,000 papers on a topic	$50

Volume discounts on higher Apify plans. The prices above are for the Apify Free plan. On paid plans the per-record price drops automatically: about 15% lower on Bronze, 25% lower on Silver and 38% lower on Gold and above.

OpenAlex usage. OpenAlex gives every network address a small shared free daily budget for keyless use, and a free API key with its own budget ($1 of OpenAlex usage a day, enough for roughly 100,000 search results or about a million filtered results). For big or frequent jobs, create a free key at openalex.org/settings/api and paste it into OpenAlex API key. Without a key, results are limited to the first 10,000 per query.

Use it via API, Make, Zapier, n8n or an AI agent

Apify API. Start a run and get the results back in one HTTP request (replace YOUR_API_TOKEN with the token from Apify Console > Settings > Integrations):

curl -X POST "https://api.apify.com/v2/acts/plotpointtech~research-papers-scraper-openalex/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query": "large language models", "yearFrom": 2024, "sortBy": "citations", "maxResults": 100}'

For longer jobs, start the run asynchronously and read the dataset when it finishes. Official apify-client libraries exist for Python and JavaScript; the API tab on this page has ready-made code.

No-code automation. Connect the tool to Make, Zapier, n8n, Google Sheets, Slack, Airtable or any webhook with Apify integrations, and use Schedules in Apify Console to run it daily or weekly (for example, sort by newest to get each week's new papers on a topic).

AI agents (MCP). Give Claude, ChatGPT, Cursor, VS Code or any MCP-compatible agent direct access to this tool through the hosted Apify MCP server. Add this server URL to your client:

https://mcp.apify.com?tools=plotpointtech/research-papers-scraper-openalex

The agent can then call the tool with the same input fields shown above and read the results.

FAQ

Is it legal to use this data? Yes. The tool does not scrape web pages. It calls the official OpenAlex API, which is published for automated use, and OpenAlex releases its data under the CC0 public-domain dedication, so you can reuse it commercially. Abstracts come from OpenAlex as published; some publishers do not allow OpenAlex to show abstracts, so those records have abstract empty. Author records contain only public academic information (names, ORCIDs, affiliations, publications). You remain responsible for how you use it under the laws that apply to you.

Is this a Google Scholar scraper? No. Google Scholar does not allow automated access. OpenAlex covers a similar range of literature (journals, repositories, preprints, books, conferences) and is free to reuse, which makes it a practical Google Scholar alternative for data work.

Why do citation counts differ from Google Scholar or Scopus? Each index covers different sources and counts citations differently. Counts here are OpenAlex's, updated continuously.

Does it download the PDFs? No. It returns pdfUrl, oaUrl and landingPageUrl so you can fetch open-access full texts yourself. Our PDF to Text tool (below) can turn those PDFs into text.

How are author names matched? A name search returns the most relevant OpenAlex author profile (set Author matches per name to see more). For exact results use ORCIDs or OpenAlex author IDs.

What if I see "daily budget is used up"? The shared keyless OpenAlex budget for the run's network address ran out. Add your free OpenAlex API key and run again.

Related tools from Plot Point Technologies

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• News Scraper - Worldwide News Search by Keyword: news coverage of a research topic or institution.
• Website to Markdown Crawler for AI, LLM & RAG: add lab and journal web pages to your RAG pipeline.

Plot Point Technologies is not affiliated with OpenAlex or OurResearch.

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If this tool saved you time, we would be grateful for a short review on this page; it helps other people find it. If something did not work as expected, please open an issue on the Issues tab and we will look into it quickly.