Google Scholar Scraper

Google Scholar Scraper

Scrape Google Scholar search results for any query, filtered by year and language. Each result includes title, authors, publication venue, year, citations, and URL. No API key or login required. Export to CSV, JSON, Excel, or XML.

Google Scholar has no official API, and scraping it yourself means handling CAPTCHAs, rate limits, and brittle HTML. This Actor reads the public search results directly, applies your year and language filters, and returns each paper as a clean, flat row. It is built for researchers, students, and anyone who needs scholarly data at scale.

Who uses it	What they scrape Google Scholar for
Academic researchers	Building a literature review dataset for a specific topic
PhD students	Tracking new papers in their field every week
Data scientists	Collecting citation data for bibliometric analysis
Librarians	Compiling publication lists for faculty or departments
Market analysts	Monitoring research output of companies or institutions

What it does

This Actor collects Google Scholar search results for a given query and returns each paper as a flat row with title, authors, publication venue, year, citations, and URL.

• 🔍 Search query: any phrase you would type into Google Scholar, from 'machine learning' to 'site:nature.com'.
• 📅 Year range filter: set yearFrom and yearTo to limit results to a publication window.
• 🌐 Language filter: choose from English, French, German, Spanish, Chinese, Japanese, Portuguese, or Russian.
• 🔢 Result cap: set maxItems to control how many papers to scrape, up to the limit of Google Scholar pagination.
• 📄 Flat output: each paper becomes one row with title, authors, venue, year, citations, and URL.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Google Scholar data

📚 Build a literature review dataset.

A researcher enters a query like 'deep learning in medicine' with yearFrom 2020 and yearTo 2025, then exports the results to CSV for screening in Excel.

📈 Track new publications weekly.

A PhD student schedules the Actor to run every Monday for their thesis topic, collecting the latest papers with citations and URLs.

🔬 Analyze citation patterns.

A data scientist scrapes thousands of papers for a bibliometric study, using the citation counts and publication years to map research trends.

🏛️ Compile faculty publication lists.

A librarian runs the Actor for each professor's name and affiliation, gathering their papers into a single spreadsheet for an annual report.

Why choose this scraper

	What you get
No official API	Google Scholar does not offer a public API, so this Actor is the easiest way to get structured data.
Clean, flat schema	Every paper is returned as a single row with consistent fields, ready for analysis.
Year and language filters	Limit results to a specific publication window or language without post-processing.
No login or API key	The Actor handles the scraping, so you do not need to authenticate or manage cookies.

How it compares

This Actor focuses on Google Scholar search results, while the competitors below cover broader Google search types or images.

Feature	ParseForge	Google Images Scraper	Google Search Scraper
Scrapes Google Scholar results	Yes	Not listed	Yes
Year range filter	Yes	Not listed	Not listed
Language filter	Yes	Not listed	Not listed
Returns citation counts	Yes	Not listed	Not listed
Returns paper authors and venue	Yes	Not listed	Not listed
Exports to CSV, JSON, Excel, XML	Yes	Yes	Yes

Configure the run

Drive the Actor with a search query, then narrow results by publication year and language. The maxItems field caps how many papers are returned. The Input tab lists every parameter.

A first run with the defaults:

{
  "searchQuery": "example",
  "language": "en",
  "yearFrom": 2020,
  "yearTo": 2025,
  "maxItems": 10
}

A larger pull:

{
  "searchQuery": "example",
  "language": "en",
  "yearFrom": 2020,
  "yearTo": 2025,
  "maxItems": 200
}

Pricing

Pay-per-result: $0.00449 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.45
1,000 results	$4.49
10,000 results	$44.90

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

1. Create a free Apify account with $5 in credit.
2. Open the Google Scholar Scraper.
3. Set your inputs and any filters, then click Start.
4. 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 Google Scholar 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/google-scholar-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Your query may be too specific, or the year range may exclude all papers. Try a broader query, widen the year range, or remove the language filter.

Why did the Actor stop before reaching maxItems?

Google Scholar may have fewer results than your maxItems, or it may have blocked further pagination. Try a different query or reduce the number of results.

Why are some fields empty?

Not all papers have complete metadata on Google Scholar. For example, some may lack a publication venue or citation count. This is normal.

Why am I getting a CAPTCHA or block?

Google may temporarily block automated requests. Wait a few minutes and try again, or reduce the frequency of your runs.

Can I search for a specific author?

Yes, use the author's name in the search query, for example 'author:John Smith'. You can also combine with topic keywords.

FAQ

Question	Answer
Does Google Scholar have an official API?	No, Google Scholar does not provide a public API. This Actor scrapes the public search results directly, so you do not need an API key.
Can I filter results by publication year?	Yes, use the yearFrom and yearTo input fields to set a range. For example, yearFrom 2020 and yearTo 2025 returns only papers published in those years.
What languages are supported?	You can filter results by language using the language field. Options include English, French, German, Spanish, Chinese, Japanese, Portuguese, and Russian.
How many results can I scrape?	Set maxItems to the number of papers you want. Google Scholar typically shows up to 1000 results per query, but the Actor will stop at your cap.
What data do I get for each paper?	Each row includes the paper title, authors, publication venue, year, citation count, and URL. The exact fields are shown in the sample output.
Do I need to log in to Google?	No, the Actor does not require a Google account or login. It accesses the public search interface.
Can I export the data?	Yes, you can export the results to CSV, JSON, Excel, or XML directly from the Apify platform.
Is this legal?	Scraping public data from Google Scholar is generally allowed for personal research, but you should review Google's terms of service and respect robots.txt for your use case.
Can I schedule this Actor to run automatically?	Yes, you can set up a schedule in Apify to run the Actor daily, weekly, or at any interval you need.
What if I get no results?	Check your search query for typos, broaden your year range, or remove the language filter. Google Scholar may also block requests if you run too many in a short time.

Related actors

• google-search-scraper: Use this if you need general Google search results, including Scholar, Images, News, and more, in one Actor.

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Google LLC. 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.