Google Scholar Profiles Scraper

Google Scholar Profiles Scraper exports public Google Scholar author profile data, citation metrics, interests, coauthors, and visible publication rows from profile URLs or user IDs.

Use it for researcher discovery, academic profile monitoring, citation snapshots, grant or hiring research, and structured profile datasets for analysis.

At a glance

• Extracts: profile URL, user ID, name, affiliation, verified email domain, interests, citations, h-index, i10-index, publication rows, optional coauthors, and scrape timestamp.
• Inputs: Google Scholar profile URLs, Google Scholar user IDs, maximum publications per profile, coauthor toggle, and proxy configuration.
• Best for: academic researcher datasets, citation metric snapshots, coauthor exploration, institutional research, and talent or grant-review workflows.
• Exports: Apify dataset rows downloadable as CSV, JSON, Excel, or available through the API.
• Login: no Google account, cookies, or Google Scholar API key are required.

What can it do?

• Export public Scholar profiles: save author identity, affiliation, verified email domain, research interests, and public profile URLs.
• Track citation metrics: collect total and since-2019 citations, h-index, and i10-index values visible on the profile.
• Capture publication rows: include visible publication titles, authors, venues, years, citation counts, and publication links up to your configured limit.
• Collect coauthor context: optionally save visible coauthor cards for lightweight research-network mapping.

Common workflows

• Build researcher shortlists: export profile metadata, citation metrics, interests, and affiliation text for candidate review.
• Monitor profile metrics: schedule repeat runs for known user IDs and compare citation or h-index changes downstream.
• Capture publication samples: limit maxPublications to the number of visible rows you need for ranking or review.
• Explore coauthor networks: enable includeCoauthors to collect visible coauthor cards from public profiles.

Example input

{
  "userIds": ["qc6CJjYAAAAJ"],
  "maxPublications": 10,
  "includeCoauthors": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Example output

{
  "profileUrl": "https://scholar.google.com/citations?user=qc6CJjYAAAAJ&hl=en",
  "userId": "qc6CJjYAAAAJ",
  "name": "Example Scholar",
  "affiliation": "Example University",
  "verifiedEmailDomain": "example.edu",
  "interests": ["machine learning", "data mining"],
  "citations": 12345,
  "hIndex": 42,
  "i10Index": 100,
  "publications": [
    {
      "title": "Example publication title",
      "authors": "A. Scholar, B. Coauthor",
      "venue": "Example Journal",
      "year": 2024,
      "citations": 25,
      "url": "https://scholar.google.com/citations?view_op=view_citation&citation_for_view=example"
    }
  ],
  "publicationCount": 1,
  "scrapedAt": "2026-07-03T09:00:00.000Z"
}

Tips for best results

• Use user IDs for stable inputs: the user= value is the cleanest identifier for repeat runs.
• Keep publication limits realistic: capture only the rows you need; larger profile pages take longer.
• Enable residential proxy if challenged: Google Scholar often blocks cloud datacenter traffic.
• Schedule gently: repeated high-volume runs can increase the chance of challenge pages.

Limits and caveats

• Only public profile data is collected: private data, login-only data, PDFs, and full paper text are not scraped.
• Google Scholar can block requests: the Actor stops with a clear challenge/rate-limit error when Scholar returns a block page.
• Metrics are page snapshots: citation counts and indexes reflect what was visible at scrape time.
• Publication rows are limited: the Actor captures visible rows from the profile up to maxPublications.

API usage

Run from the Apify API or SDK with the same input keys shown above.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/google-scholar-profiles-scraper').call({
  userIds: ['qc6CJjYAAAAJ'],
  maxPublications: 10,
  includeCoauthors: true
});
console.log(run.defaultDatasetId);

MCP and AI agents

For AI agents, use the official Apify MCP server. The focused single-Actor URL is:

https://mcp.apify.com?tools=fetch_cat/google-scholar-profiles-scraper

The default MCP server can search and run Actors. The focused URL exposes this Actor directly to clients that support tool-scoped MCP connections.

Support

If a run fails, returns no data, or a field looks wrong, open an issue from the Actor page.

Please include the Apify run ID or run URL, input JSON, one example public URL, query, or input item, what you expected, and what the dataset returned. Small reproducible inputs make parsing or site-layout issues much faster to fix.