In the ever-evolving landscape of academic research and data analysis, Google Scholar is a cornerstone for research data. It's the go-to place for scholarly articles, tracking citations, and identifying research trends. Yet, there's a significant challenge: the absence of an official Google Scholar API. This void leaves developers and researchers scrambling for Google Scholar API alternatives.
Whether you’re a developer seeking flexible scraping solutions or a researcher in pursuit of structured academic metadata, this article is your compass. I'll introduce you to the best API for Google Scholar research data and list the alternatives. Let's get started!
TL;DR - What’s the Best Google Scholar API Alternative?
If you want the quick answer: the best Google Scholar APIs fall into three main categories:
All-in-one SERP APIs: These provide structured search engine results, including Google Scholar, with easy integration and reliable proxies.
Scraping APIs: Flexible tools that let you build custom scrapers with proxy rotation, JavaScript rendering, and CAPTCHA handling.
Academic-oriented datasets: Platforms offering curated, structured academic metadata and citation data, often with their own APIs.
Among these, ScrapingBee shines as a flexible scraping API that handles proxies and anti-bot measures for you. It's ideal if you want to extract Google Scholar data your way without the hassle of managing infrastructure.
Best Google Scholar API Alternatives at a Glance
| Tool | Main features | Best for | Limitation | Pricing |
|---|---|---|---|---|
| ScrapingBee | Proxy rotation; JavaScript rendering; anti-bot bypass; CAPTCHA handling; scalable infra; raw HTML/JSON output | Developers who want full control over what Scholar data they extract | Not a structured citation API—requires parsing + custom extraction logic | From $49/mo |
| Scrapingdog | Google Scholar endpoints with structured results (JSON); simple setup | Quick integration with easier parsing | Limited customization; rate limits possible on free/lower tiers | From $40/mo |
| SearchAPI | Scholar search endpoints; accurate SERP outputs; docs/support; proxies + CAPTCHAs handled | Reliable “plug-in” Scholar SERP access | Can be pricey at scale; may not support advanced scraping | Custom |
| SerpAPI | Dedicated Scholar engine; fast responses; strong docs/community; CAPTCHA + IP rotation handled | Teams wanting a mature, well-documented SERP API | Premium pricing; limited customization beyond endpoints | From $75/mo |
| ScraperAPI | General scraping tool; robust proxy network; easy to integrate with existing scrapers | Teams that already have scrapers and need proxy infrastructure | Not specialized for Scholar; more dev effort for parsing | From $49/mo |
| WebScrapingAPI | General SERP scraping + proxy infra; JS rendering; proxy rotation | Flexible general scraping for Scholar | Not tailored for academic metadata; structuring is left to you | From $28/mo |
| ScaleSERP Google Scholar API | Scholar-specific endpoint; accurate, structured metadata; easy integration | Structured Scholar metadata via API | Less transparent pricing; may have usage limits | From $66/mo |
| Apify Google Scholar Scraper | Ready-made actor; queue handling; dataset configuration; flexible workflows | Large-scale scraping jobs with managed queues | Requires Apify platform know-how; pricing depends on usage/platform fees | From $49/mo |
| SerpWow | Scholar engine with JSON output; fast; easy API | Simple Scholar SERP pulls | Limited depth in academic metadata; not ideal for complex research | From $30/mo |
Compare The Best Google Scholar API Alternatives
When evaluating Google Scholar API alternatives, consider these key criteria:
Accuracy of the extracted data
JavaScript web scraping capabilities
Rate limits and throughput
IP rotation and anti-bot mechanisms
CAPTCHA handling
Cost and pricing models
Depth and structure of the dataset
Ease of integration and documentation quality
Below, we review the top contenders based on these factors.
1. ScrapingBee – The Best Google Scholar API

ScrapingBee's Google Scholar scraper is a powerful, flexible scraping API designed to extract data from Google Scholar and many other websites. It handles proxy rotation, JavaScript rendering, and anti-bot bypassing, so you don’t have to manage complex infrastructure.
Pros:
Easy to use with simple API calls
Supports JavaScript rendering for dynamic content
Automatic proxy rotation and CAPTCHA handling
Scalable and reliable infrastructure
Transparent pricing with pay-as-you-go plans
Cons:
Not a structured citation API; you get raw HTML or JSON that you must parse
Requires some development effort to build custom extraction logic
Pricing:
ScrapingBee offers four monthly plans from $49 to $599, scaling from 250,000 to 8,000,000 API credits and 10 to 200 concurrent requests, with higher tiers adding priority support, account management, and team features.
If you want a DIY approach with full control over what data you extract, ScrapingBee is an excellent choice.
2. Scrapingdog

Scrapingdog offers Google Scholar scraping endpoints that return structured results, making it easier to integrate into your applications.
Pros:
Structured JSON output for easier parsing
Competitive pricing
Simple setup and API usage
Cons:
Limited customization compared to flexible scrapers
May have rate limits on free or lower-tier plans
Pricing:
ScrapingDog’s main plans start around $40 per month for 200,000 request credits, scaling to about $90 for 1,000,000 and $200 for 3,000,000, with higher tiers increasing concurrency and adding priority support.
3. SearchAPI

SearchAPI provides Google Scholar search endpoints with accurate SERP outputs and good integration support.
Pros:
Reliable data extraction
Good documentation and support
Handles proxies and CAPTCHAs
Cons:
Pricing can be higher for large-scale use
May not support advanced scraping scenarios
Pricing:
SearchAPI is typically priced per 1,000 searches, with lower‑volume developer plans around a few dollars per 1,000 queries and higher‑volume production or big‑data tiers reducing that per‑1,000 rate as monthly search limits increase.
4. SerpAPI

SerpAPI is a trusted name in SERP scraping with a dedicated Scholar engine.
Pros:
Fast response times
Strong documentation and community support
Handles CAPTCHA and IP rotation automatically
Cons:
Pricing can be premium
Limited customization beyond provided endpoints
Pricing:
SerpAPI offers three monthly plans: Developer at $75 for 5,000 searches without U.S. Legal Shield, Production at $150 for 15,000 searches with U.S. Legal Shield, and Big Data at $275 for 30,000 searches with U.S. Legal Shield.
5. ScraperAPI

ScraperAPI is a general scraping tool that can be used for Google Scholar but may require more setup.
Pros:
Robust proxy network
Easy to integrate with existing scrapers
Cons:
Not specialized for Google Scholar
May require more development for parsing results
Pricing:
ScraperAPI has four main monthly plans: Hobby at $49 for 100,000 API credits and 20 concurrent threads (US/EU only), Startup at $149 for 1,000,000 credits and 50 threads (US/EU only), Business at $299 for 3,000,000 credits and 100 threads with global geotargeting, and Scaling at $475 for 5,000,000 credits and 200 threads with global geotargeting.
6. WebScrapingAPI

WebScrapingAPI offers general SERP scraping and proxy infrastructure usable for Scholar data extraction.
Pros:
Good proxy rotation
Supports JavaScript rendering
Cons:
Not tailored for academic metadata
Parsing and data structuring left to the user
Pricing:
WebScrapingAPI offers a free trial with 100 requests, then paid plans at $28/month for 10,000 requests (Starter), $130/month for 50,000 (Grow), $550/month for 250,000 (Business), and $1,600/month for 1,000,000 (Pro), all including features like global locations, SERP parsing, bulk processing, and multiple output formats.
7. ScaleSERP Google Scholar API

ScaleSERP provides a Scholar-specific endpoint with structured data fields.
Pros:
Accurate and structured metadata
Easy to integrate
Cons:
Pricing details less transparent
May have usage limits
Pricing:
ScaleSERP’s Google Scholar/Google SERP API offers annual plans at $66/month for 10,000 credits, $159/month for 50,000, and $479/month for 250,000, each allowing up to 10,000 batch requests and charging a small per‑extra‑credit overage fee.
8. Apify’s Google Scholar Scraper

Apify provides a ready-made actor for Google Scholar scraping with queue handling and dataset configuration.
Pros:
Flexible scraping workflows
Handles large-scale scraping queues
Cons:
Requires Apify platform knowledge
Pricing depends on usage and platform fees
Pricing:
Apify’s Google Scholar Scraper runs on Apify’s platform pricing: there is a free tier with a small monthly credit allowance, then paid Personal, Scale, Business, and Enterprise plans (from about $49/month upward) that give more platform credits you can spend on this scraper as needed.
9. SerpWow

SerpWow offers a Scholar engine with JSON output but limited academic metadata.
Pros:
Easy to use API
Fast responses
Cons:
Limited depth in academic metadata
May not suit complex research needs
Pricing:
SerpWow offers tiered monthly plans starting from a low-cost Hobbyist option at about $30/month for 1,000 real‑time SERP searches, scaling through Starter ($125 for 10,000), BigData ($499 for 50,000), Volume ($1,200 for 250,000), and Infrastructure tiers up to $9,000/month for 5,000,000 searches, each with overage billed per extra search and support for up to 10,000 batch jobs.
Does Google Scholar Have an Official API?

Google Scholar is a fantastic resource, but it does not provide an official API. This is primarily because Google wants to protect the integrity of its data and prevent automated scraping that could overload its servers or violate copyright rules.
Google explicitly disallows automated scraping in its terms of service, which means developers must tread carefully. However, many still need to learn how to scrape Google Scholar to access the website's data for citation analysis, trend monitoring, or research automation.
This gap has led to the rise of various SERP APIs, scrapers, and academic datasets that offer indirect or alternative access to Google Scholar’s data. SERP APIs typically provide structured search results from Google Scholar’s search engine results pages, while scrapers offer raw HTML extraction capabilities. Academic datasets, on the other hand, provide curated metadata but may not be as up-to-date or comprehensive.
About Google Scholar
Google Scholar is a free academic search engine that indexes millions of scholarly articles, theses, books, and conference papers, making it a widely used tool for citation tracking and academic discovery.
Its advantages include extensive coverage of academic literature, the availability of citation counts and related articles, and free access to abstracts and some full texts.
However, it has notable limitations: there is no official API for programmatic access, structured data export options are limited, and scraping Google Scholar is against Google's terms of service.
Google Scholar Alternatives
If you’re looking beyond Google Scholar, here are some notable platforms:
Scopus: A comprehensive abstract and citation database with strong analytics, but requires a subscription.
BASE: A large academic search engine with open-access content.
Lens.org: Integrates scholarly and patent data for research and innovation insights.
JSTOR: Archive of academic journals and books, mostly subscription-based.
Scispace: AI-powered research discovery platform.
Semantic Scholar: AI-driven academic search with citation context.
ResearchGate: Social network for researchers sharing publications and data.
Why Use a Google Scholar API?
Google Scholar API allows you to set up automated data extraction based on the parameters you use. Why would you need that? Here are a few benefits:
Automated citation analysis for academic impact studies
Trend monitoring in research topics
Building large datasets for machine learning or meta-analyses
Research automation workflows to save time and reduce manual effort
Why ScrapingBee Is the Best Google Scholar API Alternative
I already introduced what makes ScrapingBee stand out, but let me do a quick recap. It's a great tool for developers who want a flexible, scalable scraping solution without the headache of managing proxies or browser automation. It offers:
AI scraping that adapts to site changes
Built-in proxy rotation and CAPTCHA bypass
JavaScript rendering for dynamic pages
Additional features like the Screenshot API for visual validation
Real-world workflows show how this API can streamline Google Scholar data extraction, making it a top choice for hands-on developers.
Try Scraping Google Scholar with ScrapingBee Today
Ready to get started? ScrapingBee makes it easy to scrape Google Scholar data without worrying about proxies or complex setups. Sign up now to test our API and see how quickly you can integrate academic search data into your projects.
Google Scholar API FAQs
Can I use Google Scholar for free?
Yes, Google Scholar is free to use for searching academic literature, but programmatic access via an official API is not available.
Can I scrape full articles on Google Scholar?
Google Scholar primarily indexes metadata and abstracts. Full articles are often behind paywalls or hosted on publisher sites, so scraping full texts is generally not feasible or legal.
Do you need proxies for scraping Google Scholar?
Yes, proxies and IP rotation are essential to avoid bans and CAPTCHAs when scraping Google Scholar.
Is web scraping legal for Google Scholar research?
Scraping Google Scholar violates Google’s terms of service. While many researchers use scraping for academic purposes, it’s important to consider legal and ethical implications and use scraping responsibly.

Kevin worked in the web scraping industry for 10 years before co-founding ScrapingBee. He is also the author of the Java Web Scraping Handbook.


