How to Scrape Google Scholar with JavaScript

Google Scholar contains valuable data — paper title, authors, citation count, abstract snippet, and more. Scraping this data directly means dealing with anti-bot detection, CAPTCHAs, IP rotation, and constantly breaking selectors. The Scavio API handles all of that and returns clean, structured JSON from a single POST request.

This tutorial shows you how to scrape Google Scholar using JavaScript and the Scavio API. By the end, you will have a working JavaScript script that fetches real-time Google Scholar data and parses the results.

Prerequisites

• JavaScript installed on your machine
• A Scavio API key (free tier includes 500 credits/month — no credit card required)

Step 1: Install Dependencies

fetch is built into JavaScript, so there is nothing to install.

# No installation needed — fetch is built into Node.js 18+

Step 2: Make Your First Google Scholar Search

Send a POST request to the Scavio Google Scholar API endpoint with your query. The API returns structured JSON with paper title, authors, citation count, and more.

const API_KEY = "your_scavio_api_key";

const response = await fetch("https://api.scavio.dev/api/v1/search", {
  method: "POST",
  headers: {
    "x-api-key": API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ query, tbs: "" }),
});

const data = await response.json();
for (const result of data.organic_results?.slice(0, 5) ?? []) {
  console.log(`${result.position}. ${result.title}`);
  console.log(`   ${result.link}\n`);
}

Step 3: Example Response

The API returns structured JSON. Here is an example response for a Google Scholar search:

{
  "search_metadata": { "status": "success" },
  "organic_results": [
    {
      "position": 1,
      "title": "Retrieval-Augmented Generation for Large Language Models: A Survey",
      "link": "https://scholar.google.com/scholar?hl=en&q=retrieval+augmented+generation",
      "authors": ["Y. Gao", "Y. Xiong", "X. Gao"],
      "publication_year": 2024,
      "cited_by": 1240,
      "snippet": "We survey RAG approaches that combine parametric and non-parametric memory..."
    }
  ]
}

Every field is structured and typed — no HTML parsing, no CSS selectors, no regex extraction. Your JavaScript code can access any field directly.

Step 4: Full Working Example

Here is a complete, runnable JavaScript script that searches Google Scholar and prints the results:

/**
 * Scrape Google Scholar search results using Scavio API.
 * Returns structured JSON with paper title, authors, citation count, and more.
 */
const API_KEY = "your_scavio_api_key";

async function searchGoogleScholar(query) {
  const response = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST",
    headers: {
      "x-api-key": API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ query, tbs: "" }),
  });

  if (!response.ok) {
    throw new Error(`Scavio API error: ${response.status}`);
  }

  return response.json();
}

const results = await searchGoogleScholar("retrieval augmented generation 2024");
console.log(JSON.stringify(results, null, 2));

Why Use Scavio Instead of Scraping Google Scholar Directly?

• No proxy management. Direct scraping requires rotating proxies to avoid IP bans. Scavio handles all of this server-side.
• No CAPTCHA solving. Google Scholar aggressively blocks automated requests. Scavio returns clean data every time.
• Structured JSON output. No HTML parsing or CSS selector maintenance. Get typed, consistent data from every request.
• Multi-platform in one API. Search Google, Amazon, YouTube, and Walmart from the same API key with the same authentication pattern.
• Free tier included. 500 credits/month with no credit card required. Each search costs 1 credit.