9 Best Google Scholar Scrapers in 2026 (Updated)

Academic research moves fast, and manually collecting data from Google Scholar can feel like running a marathon in flip-flops. If you've ever spent hours copying citations or clicking through endless search results, you know the pain. Google Scholar scrapers are specialized tools that automatically extract citations, abstracts, and metadata, turning days of work into minutes.

The challenge isn't just finding any scraper—it's finding one that actually works reliably without getting blocked by Google's anti-bot systems. Modern scraping tools handle proxy rotation, CAPTCHA solving, and data structuring automatically, so you can focus on your research instead of babysitting a script.

Why You Need a Google Scholar Scraper

Let's be real: Google Scholar doesn't offer an official API. Researchers, data scientists, and academic institutions need systematic ways to collect scholarly data for bibliometric analysis, literature reviews, or citation tracking. Manual collection is slow and error-prone, especially when you're dealing with hundreds or thousands of papers.

A good scraper should extract titles, authors, publication dates, citation counts, and source links efficiently while respecting rate limits and avoiding IP bans. The tools below do exactly that, each with its own strengths depending on your specific needs.

1. Apify

Apify Google Scholar Scraper eliminates the API problem entirely. This platform-based solution extracts comprehensive academic data including titles, authors, citations, publication dates, and source details directly from search results. The interface is straightforward—you configure your search parameters, hit run, and export your data in JSON, CSV, or Excel.

Pricing: Free plan with $5 monthly credits; paid plans scale with usage

What makes it stand out:

• Advanced filtering by date range and document type

• API integration with Python and Node.js for automation

• Custom webhook support for real-time notifications

• Related article extraction for deeper research

• Built-in proxy management handles the technical headaches

2. ScraperAPI

When you need a robust solution that just works, ScraperAPI delivers. This service specializes in handling the messy technical challenges that make web scraping difficult—proxy management, browser rendering, and those annoying CAPTCHAs. The API uses smart algorithms to bypass anti-bot measures while maintaining high success rates.

For researchers dealing with large-scale data collection, 👉 ScraperAPI offers enterprise-grade infrastructure that handles millions of requests reliably. The automatic retry system means failed requests don't derail your entire scraping job.

Pricing: Free plan with 1,000 API calls; paid plans start at $29/month for 250,000 calls

Core capabilities:

• Automatic proxy rotation keeps you unblocked

• Built-in CAPTCHA solving saves time and frustration

• JSON structured data extraction for easy processing

• IP geotargeting for location-specific results

• 24/7 technical support when things go sideways

• Customizable request headers for advanced users

3. SerpAPI

SerpAPI takes a different approach by providing real-time access to Google Scholar data through a well-documented API. The service handles all the backend complexity while delivering clean, structured data. If you're building applications that need live academic search data, this is your tool.

Pricing: Free plan with 100 monthly searches; paid plans start at $50/month for 5,000 searches

Key strengths:

• Automatic parsing of citations, abstracts, and author info

• JSON output integrates smoothly with any workflow

• Location-specific search results for regional research

• 99.9% uptime guarantee for production environments

• Official libraries for multiple programming languages

• Comprehensive documentation with working code examples

4. Oxylabs

Oxylabs Google Scholar Scraper API is built for serious data extraction at scale. This enterprise-focused solution handles proxy rotation, CAPTCHA solving, and JavaScript rendering without you lifting a finger. The API is particularly strong when you need consistent, high-volume data collection.

Pricing: Custom plans starting from $100/month based on request volume

Notable features:

• High success rates with automatic retry logic

• Real-time extraction for time-sensitive research

• Python integration with detailed documentation

• Advanced parsing for titles, authors, citations, and URLs

• Geolocation targeting for global research projects

• 24/7 customer support for enterprise clients

5. MahdiNavaei

Sometimes you just need a simple, no-frills solution. This Python-based program does exactly what it says on the tin: extracts academic articles from Google Scholar using titles or keywords. It's open-source, straightforward, and perfect for researchers comfortable with basic Python scripting.

Pricing: Free and open-source

What you get:

• Article extraction based on titles or keywords

• Simple Python implementation for easy customization

• Direct interface for academic research

• Metadata collection capabilities

• Community support through GitHub

• Works in standard Python environments

6. Octoparse

Not everyone wants to write code. Octoparse is a visual web scraping tool that lets you extract Google Scholar data through pointing and clicking. The platform comes with pre-built templates specifically designed for academic data extraction, making it accessible even if you've never written a line of code.

Pricing: Free plan available; paid plans start at $75/month

User-friendly features:

• No-code visual interface for data selection

• Pre-built Google Scholar template saves setup time

• AI-powered auto-detection of data elements

• Automated task scheduling for regular scraping

• Cloud-based extraction runs without your computer

• Built-in IP rotation prevents blocks

7. scholarly Python Library

The scholarly Python package is a developer favorite for good reason. This free, open-source library provides a clean interface for accessing Google Scholar data through simple Python commands. It handles request complexity and response parsing automatically, letting you focus on analysis instead of infrastructure.

Pricing: Completely free and open-source

Developer-friendly features:

• Retrieves author profiles with h-index and citation counts

• Searches for papers and extracts metadata efficiently

• Gets citation counts and bibliographic information

• Automatic pagination handling for large result sets

• Built-in rate limiting prevents blocking

• No API keys or authentication required

• Proxy support for larger scraping operations

8. Scrape-Helper Toolset

Scrape-Helper Toolset offers a lightweight solution designed specifically for Google Scholar. The tool uses smart proxy rotation and request handling to stay under Google's radar while collecting your data. If you need something between a full programming library and a no-code tool, this fits the bill.

Pricing: Basic plan starts at $49/month with 1,000 requests; free trial available

Practical features:

• Built-in proxy management system

• Point-and-click interface for ease of use

• Export to CSV, JSON, and Excel formats

• Automatic citation parsing

• Custom search filters and parameters

• Rate limiting protection

• Multi-language support

• Regular compatibility updates

9. Google Search Results Extractor

While not exclusively for Google Scholar, this Apify-based scraper excels at extracting structured data from Google Search Results Pages. It transforms messy search results into organized formats, making it useful for researchers who need broader search data beyond just Scholar results.

Pricing: Credit-based through Apify platform; free plan available, paid plans start at $49/month

Versatile capabilities:

• Automatic CAPTCHA handling and IP rotation

• Multiple output formats including JSON and Excel

• Support for multiple languages and regions

• Advanced filtering for specific SERP elements

• Real-time data extraction

• Featured snippet and knowledge graph extraction

• Mobile and desktop search result support

Choosing Your Google Scholar Scraper

The right tool depends on your specific situation. If you're a researcher needing occasional data extraction, Apify offers the most comprehensive feature set with flexible pricing. For developers building applications, the scholarly Python library provides excellent value as a free, well-maintained option.

When you're running large-scale operations that demand reliability and enterprise support, 👉 tools like ScraperAPI provide the infrastructure and support needed for mission-critical data collection. Their automatic retry systems and proxy management mean you can focus on analyzing data instead of maintaining scraping infrastructure.

For non-technical users, Octoparse removes the coding barrier entirely with its visual interface and pre-built templates. And if budget is your primary concern, open-source options like MahdiNavaei and scholarly deliver solid functionality without ongoing costs.

The academic research landscape continues evolving, and having the right data extraction tools can make the difference between spending weeks on literature reviews or completing them in days. Whatever your research needs, one of these scrapers should fit your workflow and help you collect the scholarly data you need efficiently.