Does Google Scholar have an official API?

No. Google doesn't provide one. SerpKite returns the public Scholar results page as structured JSON.

Can I get citation counts?

Yes, cited_by is the number Google Scholar shows for each result.

Do all results have PDFs?

No. pdf_url is set only when Scholar links a freely available PDF.

How much does the Google Scholar API cost?

1 credit per page of 10 results, $0.60 to $1.00 per 1,000 calls. Empty result pages are free.

Can I filter by year?

Add year filters to the query using Scholar's syntax, or post-filter on the parsed year field.

POST /v1/scholar

Google Scholar API

Search Google Scholar and get papers with publication info, year, citation count and a direct PDF link when one exists. Google Scholar has no official API; this is the structured version of its results page.

Get a free API key Try in playground

1 credit per page of 10 results 2,500 free credits, no card Failed calls are free

Overview

What the Google Scholar API does

Google Scholar doesn't offer an API. SerpKite's Google Scholar API returns the public results page as JSON: title, link, publication_info (authors, venue, year as Google formats it), a parsed year, cited_by count, snippet and pdf_url when Scholar links a free PDF.

For research agents, combine it with the Webpage to Markdown API to read a paper's landing page, or use format=markdown to drop a literature list straight into a prompt.

What you get

results[] array: position, title, link, domain, publication_info, snippet, year, cited_by, pdf_url, id.
request object: Echo of the normalized request (endpoint, engine, q, country, language, page…), handy for logging.
meta object: request_id, credits_used, cached, engine, latency_ms, resolved_urls and parse_quality. parse_quality=empty means the call was not billed.

Request

POST /v1/scholar

cURL

Python

TypeScript

fetch

PHP

curl https://api.serpkite.com/v1/scholar \
  -H "Authorization: Bearer $SERPKITE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"q":"retrieval augmented generation"}'

Response (illustrative, placeholder domains)

200 OK · application/json

{
  "request": {
    "endpoint": "scholar",
    "engine": "google",
    "q": "retrieval augmented generation",
    "language": "en",
    "page": 1
  },
  "results": [
    {
      "position": 1,
      "title": "Retrieval-augmented generation for knowledge-intensive NLP tasks",
      "link": "https://papers.example.org/rag-knowledge-intensive",
      "domain": "papers.example.org",
      "publication_info": "A Author, B Author, C Author - Advances in Neural Information Processing Systems, 2020",
      "snippet": "Large pre-trained language models have been shown to store factual knowledge in their parameters…",
      "year": 2020,
      "cited_by": 9800,
      "pdf_url": "https://papers.example.org/rag-knowledge-intensive.pdf",
      "id": "a1B2c3D4e5F6"
    },
    {
      "position": 2,
      "title": "A survey on retrieval-augmented text generation",
      "link": "https://journal.example.edu/rag-survey",
      "domain": "journal.example.edu",
      "publication_info": "D Author, E Author - arXiv preprint, 2024",
      "year": 2024,
      "cited_by": 640
    }
  ],
  "meta": {
    "request_id": "req_01J8ZK4M6Q2V7",
    "credits_used": 1,
    "engine": "google",
    "cached": false,
    "latency_ms": 812,
    "resolved_urls": true,
    "parse_quality": "ok"
  }
}

Every response also carries X-Credits-Used, X-Credits-Remaining, X-Cache and X-Tokens-Estimate headers. Run this query in the playground

Reference

Parameters

The parameters /v1/scholar accepts, in the JSON body or the query string.

Google Scholar API parameters
Name	Type	Default	Description
`q` required	string	–	The search query. Required. Up to 2,048 characters.
`language`	string	en	Interface language, as a language code (en, de, fr, pt-BR…).
`num`	integer	10	Results per call. 10 per page; 100 fetches the top 100 as a depth bundle for 7 credits instead of 10. Values: 10, 20, 30, 50, 100.
`page`	integer	1	Results page, 1–10. Each page is billed separately.
`format`	string	json	Response format. markdown is LLM-ready prose; compact is JSON with only the fields agents need. Values: json, compact, markdown.
`fields`	string	–	Comma-separated projection, e.g. results.title,results.link,knowledge_graph. Cuts tokens.
`max_age`	integer	–	Accept a cached result up to this many seconds old. Cache hits cost 50% of the credits.

Full reference, error codes and headers are in the API docs. Send a JSON array of up to 100 request objects to run them in one call.

Use cases

What people build with the Google Scholar API

Literature review agents

Find the most-cited papers on a topic and summarize them.

Citation tracking

Track citation counts for your lab's papers over time.

Research datasets

Build paper lists with PDF links for downstream processing.

Expert discovery

Find who publishes most on a niche topic.

Pricing