Google Scholar Scraper

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A robust, high-performance utility designed for developer automation, data integration, and AI training. Features built-in captcha bypass, headful/headless browser execution, and proxy support to scrape Google data seamlessly, reliably, and at scale.

Pricing

from $4.99 / 1,000 results

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0.0

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Coding Frontned

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Monthly active users

15 days ago

Last modified

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Automation

Developer tools

Extracts public Google Scholar search results with lightweight native HTTPS requests and Cheerio parsing. It does not open publication pages, bypass paywalls, access private profiles, or download PDFs.

{
  "queries": ["attention is all you need", "retrieval augmented generation"],
  "maxItems": 10,
  "maxPages": 2,
  "maxTotalItems": 20,
  "yearFrom": 2020,
  "sortBy": "relevance",
  "language": "en"
}

Use legacy query for one search or queries for up to ten. maxItems is a per-query cap, maxPages is a per-query request cap, and maxTotalItems is the hard aggregate cap. Results are deduplicated per query using Scholar's result ID, or a stable title/link/author hash when Scholar omits it.

Output includes title and publication link when available, result type, snippet, author line/names/public profiles, venue/publisher/year, citation and version counts with Scholar URLs, related/cached links, open-access side link and label, rank/page/query metadata, request provenance, and scrapedAt. Missing optional values are omitted rather than represented with placeholders or nulls.

Direct requests are the default. Optional proxyConfiguration accepts standard Apify settings; a two-letter country becomes the proxy country hint. CAPTCHA, consent, unusual-traffic, 403, and 429 responses are rejected and retried within a strict limit; they are never stored as records.

Run locally with npm ci, npm run lint, npm test, apify run --purge --input-file qa-inputs/local-search.json, and npm run validate. Use qa-inputs/cloud-validation.json for a bounded cloud check.