Google Scholar Scraper

Google Scholar results by keyword: title, URL, authors, venue, year, source site, and citation count.

For researchers, students, and AI builders who collect literature. Every run tells you plainly what worked and what did not: no silent empty runs.

What you can do with it

• Literature lists: collect papers for a topic with authors, year, and venue.
• Citation checks: sort by citedBy to find the most cited work.
• RAG source lists: feed paper URLs to your reading pipeline.

What you get

Field	What it is	Example
query	The search term that produced this row.	large language models
type	article, pdf, book, or error.	article
position	1-based rank in this Actor's list.	1
page	Scholar results page number.	1
title	Paper or book title.	Beyond efficiency: A systematic survey of resource-efficient large la…
url	Paper URL.	https://dl.acm.org/doi/abs/10.1145/3845797
description	Abstract excerpt.	… Beyond Eficiency: A Systematic Survey of Resource-Eficient Large La…
publication	Full publication line as Scholar shows it.	G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang… - ACM Computing …, 2026…
authors	Author names as Scholar lists them (Scholar shortens long lists).	[G Bai, …]
venue	Journal, book, or conference name as shown.	ACM Computing
year	Publication year.	2026
sourceSite	Site that hosts the item, for example JSTOR or books.google.com.	dl.acm.org
citedBy	Citation count when present.	275
pdfUrl	Direct PDF link when the parser returns one.	https://dl.acm.org/doi/pdf/10.1145/3845797
rankOrganic	Position among organic results on the results page.	1

Examples come from a real run. Every row has every field; a value the page did not show is null, never guessed.

How to use it

1. Click Try for free (or Start) on this page.
2. Enter one search query per line in the first field. The form is prefilled with a working example.
3. Optional: set Max results and the other options.
4. Click Start. Open the Output tab, or export JSON, CSV, Excel, or HTML.

Example input

{
  "queries": [
    "large language models"
  ],
  "pages": 1,
  "maxResults": 3
}

Example output

One real row from a run on 26 October 2026 (long values shortened here):

{
  "query": "large language models",
  "type": "article",
  "position": 1,
  "page": 1,
  "title": "Beyond efficiency: A systematic survey of resource-efficient large language models",
  "url": "https://dl.acm.org/doi/abs/10.1145/3845797",
  "description": "… Beyond Eficiency: A Systematic Survey of Resource-Eficient Large Language Models • 19 \nIn this condensed examination of resource eiciency in Large Language…",
  "publication": "G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang… - ACM Computing …, 2026 - dl.acm.org",
  "authors": [
    "G Bai",
    "Z Chai",
    "C Ling",
    "…"
  ],
  "venue": "ACM Computing",
  "year": 2026,
  "sourceSite": "dl.acm.org",
  "citedBy": 275,
  "pdfUrl": "https://dl.acm.org/doi/pdf/10.1145/3845797",
  "rankOrganic": 1
}

Pricing

Pay per result: $0.50 per 1,000 rows, plus $0.001 per run start. No subscription.

Event	When	Price
Actor start	Once per run (per GB of memory; the default 256 MB counts as one)	$0.001
Result row	Each row saved to the dataset	$0.0005

Example	Rows	Cost
10 papers	10	$0.001 + $0.005 = $0.006
100 papers	100	$0.001 + $0.05 = $0.051
1,000 papers	1,000	$0.001 + $0.50 = $0.501

• Retries after a bot check or a temporary error cost you nothing. You pay only for rows saved.
• An input that fails after all retries saves one error row (one row charge), so you can see what failed and why.
• On Apify's free plan a run stops at 20 rows. Any paid Apify plan removes this limit.
• Set Max total charge per run in the run options. The Actor stops cleanly at that limit and keeps every row saved so far.

What you can count on

• Same columns on every row. Missing values are null, so spreadsheets and databases never break.
• No silent failures. An input that fails gets an error row with errorCode and a plain-language errorMessage. The other inputs keep running.
• A clear run summary. The run status says how many results were saved, how many inputs failed, and why. The same numbers are saved as the RUN_SUMMARY record in the run's key-value store, for automations.
• Automatic retries. Bot checks and temporary errors are retried with a fresh request before an input counts as failed.
• Limits respected. Max results and your spending limit stop the run cleanly.

Use it from code, automations, and AI agents

API (returns the rows when the run finishes):

curl -X POST "https://api.apify.com/v2/acts/plumblinedata~google-scholar-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries": ["large language models"], "pages": 1, "maxResults": 3}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("plumblinedata/google-scholar-scraper").call(run_input={"queries": ["large language models"], "pages": 1, "maxResults": 3})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row)

JavaScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('plumblinedata/google-scholar-scraper').call({"queries": ["large language models"], "pages": 1, "maxResults": 3});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

No-code: connect the Actor in Make, Zapier, n8n, or Google Sheets through Apify's integrations, or add a webhook to get notified when a run finishes.

AI agents (MCP): add https://mcp.apify.com?tools=plumblinedata/google-scholar-scraper to Claude, Cursor, or any MCP client. The agent can call this Actor as a tool with the same input as above.

Limitations

• Scholar shortens long author and venue lists; they are kept as shown.
• pdfUrl is set only when Scholar shows a PDF link.

FAQ

Do I get the abstract or full text? You get the snippet Scholar shows (description), not the full paper. pdfUrl links to the PDF when Scholar has one.

Can I find the most cited papers on a topic? Yes. Run your topic, then sort the dataset by citedBy.

What does an error row mean? It marks an input that failed after retries. errorCode is short (blocked, empty_result, not_available, http_404, or invalid_... for a bad ID or URL) and errorMessage says what to do. Remove error rows with a filter on type.

Can I run it on a schedule? Yes. Create a task with your input in Apify Console, then add a schedule (for example every day at 8:00).

Is it legal to collect this data? The Actor reads public pages that anyone can open without logging in. You are responsible for how you use the data, including copyright, personal data rules such as GDPR, and the site's terms. If you are not sure, ask a lawyer.

Related Actors

• Google Search Scraper: Google search results as rows.
• Google News Scraper: Google News results by keyword.

Support

Found a problem or need a field? Open an issue on the Issues tab. Include the run ID and one input that shows the problem. We read every issue.