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Best Google Scholar API Alternatives - Get Ready for 2026

19 January 2026 | 10 min read

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:

  1. All-in-one SERP APIs: These provide structured search engine results, including Google Scholar, with easy integration and reliable proxies.

  2. Scraping APIs: Flexible tools that let you build custom scrapers with proxy rotation, JavaScript rendering, and CAPTCHA handling.

  3. 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

ToolMain featuresBest forLimitationPricing
ScrapingBeeProxy rotation; JavaScript rendering; anti-bot bypass; CAPTCHA handling; scalable infra; raw HTML/JSON outputDevelopers who want full control over what Scholar data they extractNot a structured citation API—requires parsing + custom extraction logicFrom $49/mo
ScrapingdogGoogle Scholar endpoints with structured results (JSON); simple setupQuick integration with easier parsingLimited customization; rate limits possible on free/lower tiersFrom $40/mo 
SearchAPIScholar search endpoints; accurate SERP outputs; docs/support; proxies + CAPTCHAs handledReliable “plug-in” Scholar SERP accessCan be pricey at scale; may not support advanced scrapingCustom
SerpAPIDedicated Scholar engine; fast responses; strong docs/community; CAPTCHA + IP rotation handledTeams wanting a mature, well-documented SERP APIPremium pricing; limited customization beyond endpointsFrom $75/mo
ScraperAPIGeneral scraping tool; robust proxy network; easy to integrate with existing scrapersTeams that already have scrapers and need proxy infrastructureNot specialized for Scholar; more dev effort for parsingFrom $49/mo
WebScrapingAPIGeneral SERP scraping + proxy infra; JS rendering; proxy rotationFlexible general scraping for ScholarNot tailored for academic metadata; structuring is left to youFrom $28/mo
ScaleSERP Google Scholar APIScholar-specific endpoint; accurate, structured metadata; easy integrationStructured Scholar metadata via APILess transparent pricing; may have usage limitsFrom $66/mo
Apify Google Scholar ScraperReady-made actor; queue handling; dataset configuration; flexible workflowsLarge-scale scraping jobs with managed queuesRequires Apify platform know-how; pricing depends on usage/platform feesFrom $49/mo
SerpWowScholar engine with JSON output; fast; easy APISimple Scholar SERP pullsLimited depth in academic metadata; not ideal for complex researchFrom $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

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

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

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

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

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

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

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

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

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?

Scholar

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.

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.

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Kevin Sahin

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.