Google Scholar Scraper API

Search Query

Name

q

Required

Required

Description

Parameter defines the query you want to search. You can use anything that you would use in a regular Google Scholar search. e.g. source:, author:. Parameter is not required if cites or cluster parameter is present.
Name

cites

Required

Optional

Description

The cites parameter is used to specify a unique ID for an article. Utilizing this parameter will generate a list of documents in Google Scholar that cite the specified article. For instance, cites=13392090434137936466 could be used to find all documents that cite the article with this unique ID. Additionally, using both the cites and q parameters together will result in a search within the citing articles themselves.
Name

cluster

Required

Optional

Description

The cluster parameter is used to specify a unique ID for an article. Utilizing this parameter will generate a list of document versions in Google Scholar that are related to the specified article.
Note: When the q and cluster parameters are used together, they are not compatible. In such cases, priority is given to the q parameter.

Localization

Name

hl

Required

Optional

Description

The default parameter en defines the interface language of the search. Check the full list of supported Google hl languages.
Name

lr

Required

Optional

Description

The lr parameter restricts search results to documents written in a particular language or a set of languages. The accepted format for this parameter is lang_{2-letter country code}. For instance, to filter documents written in Japanese, the value should be set to lang_jp. To incorporate multiple languages, a value like lang_it|lang_de restricts the search to documents written in either Italian or German. Google identifies the document language based on the top-level domain (TLD) of the document's URL, any language meta tags present, or the language utilized within the document's body text. Check the full list of supported Google lr languages.

Filters

Name

scisbd

Required

Optional

Description
Default value 0 returns all results sorted by relevance. There are two other options:
- 1 - includes only abstracts, filters articles added in the last year, and sorts by date.
- 2 - filters articles added in the last year and sorts by date.
Note: scisbd=1 and scisbd=2 values are not compatible with as_ylo or as_yhi parameters.
Name

as_ylo

Required

Optional

Description

Parameter sets the start year to filter results. Pair with as_yhi for a specific end year. Input format: YYYY. E.g., as_ylo=2022 fetches results from 2022 onwards.
Name

as_yhi

Required

Optional

Description

Parameter sets the start year to filter results. Pair with as_yhi for a specific end year. Input format: YYYY. E.g., as_yhi=2022 fetches results till 2022 backwards.
Name

as_rr

Required

Optional

Description

Default value 0 returns all results. Use 1 to return results only with review articles.
Name

as_vis

Required

Optional

Description

Default value 0 returns results with citations. Use 1 to return results without citations.
Name

as_sdt

Required

Optional

Description
This parameter works as a filter for patents or as filter for US court law. By default, 0 returns results without patents.
Patent Filter Values:
- 0 - Excludes patents (default).
- 7 - Includes patents.
US Courts Law Search Types:
- 4 - All US courts. For specific courts, append values after 4 separated by commas (e.g., 4,1 for Alabama courts or 4,192 for tax federal court).
- ffffffffffffe04 - All US state courts.
- 3 - All US federal courts.
See a complete list of Google Scholar supported courts.
Name

filter

Required

Optional

Description

This parameter controls whether the "Duplicate Content" and "Host Crowding" filters are enabled. Set the value to 1 to enable these filters, which is the default setting. To disable these filters, set the value to 0.
Name

safe

Required

Optional

Description

This parameter toggles the SafeSearch feature for the results. SafeSearch operates by filtering out adult content from your search results. Google's filters use proprietary technology to check keywords, phrases and URLs. While no filters are 100 percent accurate, SafeSearch will remove the overwhelming majority of adult content from your search results. Set the value to active to enable SafeSearch. To disable it, set the value to off. By default, SafeSearch is disabled.
Name

source

Required

Optional

Description

This parameter allows filtering of organic results based on a specific source. It is added to the q parameter and is not compatible with cites or cluster parameters.

Pagination

Name

num

Required

Optional

Description

This parameter specifies the number of results to display per page. By default, it is set to 10, maximum number - 20. Use in combination with the page parameter to implement pagination functionality.
Name

page

Required

Optional

Description

This parameter indicates which page of results to return. By default, it is set to 1. Use in combination with the num parameter to implement pagination.

Engine

Name

engine

Required

Required

Description

Parameter defines an engine that will be used to retrieve real-time data. It must be set to google_scholar.

API key

Name

api_key

Required

Required

Description

The api_key authenticates your requests. Use it as a query parameter (https://www.searchapi.io/api/v1/search?api_key=YOUR_API_KEY) or in the Authorization header (Bearer YOUR_API_KEY).

Full Response

GET

https://www.searchapi.io/api/v1/search?engine=google_scholar&q=Langchain

Request

import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_scholar",
  "q": "Langchain"
}

response = requests.get(url, params=params)
print(response.text)

Response

{
  "search_metadata": {
    "id": "search_AxENYzjKgR4PcjaK3D0M4GJb",
    "status": "Success",
    "created_at": "2023-08-14T14:21:25Z",
    "request_time_taken": 1.27,
    "parsing_time_taken": 0.03,
    "total_time_taken": 1.3,
    "request_url": "https://scholar.google.com/scholar?q=Langchain&hl=en",
    "html_url": "https://www.searchapi.io/api/v1/searches/search_AxENYzjKgR4PcjaK3D0M4GJb.html",
    "json_url": "https://www.searchapi.io/api/v1/searches/search_AxENYzjKgR4PcjaK3D0M4GJb"
  },
  "search_parameters": {
    "engine": "google_scholar",
    "q": "Langchain",
    "google_domain": "google.com",
    "hl": "en"
  },
  "search_information": {
    "query_displayed": "Langchain",
    "total_results": 411,
    "page": 1,
    "time_taken_displayed": 0.07
  },
  "organic_results": [
    {
      "position": 1,
      "title": "Creating Large Language Model Applications Utilizing LangChain: A Primer on Developing LLM Apps Fast",
      "data_cid": "QXV-Nxym8hQJ",
      "link": "https://as-proceeding.com/index.php/icaens/article/view/1127",
      "publication": "O Topsakal, TC Akinci - International Conference on Applied …, 2023 - as-proceeding.com",
      "snippet": "… LangChain has been widely recognized in the AI community for its ability … LangChain and provide a primer on developing large language model applications rapidly utilizing LangChain…",
      "inline_links": {
        "cached_page_link": "https://scholar.googleusercontent.com/scholar?q=cache:QXV-Nxym8hQJ:scholar.google.com/+Langchain&hl=en&as_sdt=0,5"
      },
      "resource": {
        "name": "as-proceeding.com",
        "format": "PDF",
        "link": "https://as-proceeding.com/index.php/icaens/article/download/1127/1062"
      },
      "authors": [
        {
          "name": "O Topsakal",
          "id": "ukpd7PsAAAAJ",
          "link": "https://scholar.google.com/citations?user=ukpd7PsAAAAJ&hl=en&oi=sra"
        },
        ...
      ]
    },
    ...
  ],
  "pagination": {
    "current": 1,
    "next": "https://scholar.google.com/scholar?start=10&q=Langchain&hl=en&as_sdt=0,5",
    "other_pages": {
      "2": "https://scholar.google.com/scholar?start=10&q=Langchain&hl=en&as_sdt=0,5",
      ...
    }
  }
}

Cluster Search

GET

https://www.searchapi.io/api/v1/search?cluster=10342765531442280392&engine=google_scholar

Request

import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_scholar",
  "cluster": "10342765531442280392"
}

response = requests.get(url, params=params)
print(response.text)

Response

{
  "search_metadata": {
    "id": "search_RqXLK4ZloPW8i54BgxM8z2jE",
    "status": "Success",
    "created_at": "2023-08-09T14:17:59Z",
    "request_time_taken": 1.3,
    "parsing_time_taken": 0.02,
    "total_time_taken": 1.31,
    "request_url": "https://scholar.google.com/scholar?hl=en&cluster=10342765531442280392",
    "html_url": "https://www.searchapi.io/api/v1/searches/search_RqXLK4ZloPW8i54BgxM8z2jE.html",
    "json_url": "https://www.searchapi.io/api/v1/searches/search_RqXLK4ZloPW8i54BgxM8z2jE"
  },
  "search_parameters": {
    "engine": "google_scholar",
    "google_domain": "google.com",
    "hl": "en",
    "cluster": "10342765531442280392"
  },
  "search_information": {
    "total_results": 5,
    "time_taken_displayed": 0.02
  },
  "organic_results": [
    {
      "position": 1,
      "title": "OpenAI ChatGPT generated literature review: Digital twin in healthcare",
      "data_cid": "yHfF2HPiiI8J",
      "link": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4308687",
      "publication": "Ö Aydın, E Karaarslan - Available at SSRN 4308687, 2022 - papers.ssrn.com",
      "snippet": "Literature review articles are essential to summarise the related work in the selected field. However, covering all related studies takes too much time and effort. This study questions …",
      "inline_links": {
        "cited_by": {
          "cites_id": "10342765531442280392",
          "total": 135,
          "link": "https://scholar.google.com/scholar?cites=10342765531442280392&as_sdt=5,47&sciodt=0,47&hl=en"
        },
        "related_articles_link": "https://scholar.google.com/scholar?q=related:yHfF2HPiiI8J:scholar.google.com/&scioq=&hl=en&as_sdt=0,47"
      },
      "authors": [
        {
          "name": "Ö Aydın",
          "id": "cX5ncpcAAAAJ",
          "link": "https://scholar.google.com/citations?user=cX5ncpcAAAAJ&hl=en&oi=sra"
        },
        ...
      ]
    },
    ...
  ]
}

Cites Search

GET

https://www.searchapi.io/api/v1/search?cites=10342765531442280392&engine=google_scholar

Request

import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_scholar",
  "cites": "10342765531442280392"
}

response = requests.get(url, params=params)
print(response.text)

Response

{
  "search_metadata": {
    "id": "search_AEM9arelpd2kFE2QoW0Nw8nB",
    "status": "Success",
    "created_at": "2023-08-09T14:19:11Z",
    "request_time_taken": 1.44,
    "parsing_time_taken": 0.03,
    "total_time_taken": 1.47,
    "request_url": "https://scholar.google.com/scholar?hl=en&cites=10342765531442280392",
    "html_url": "https://www.searchapi.io/api/v1/searches/search_AEM9arelpd2kFE2QoW0Nw8nB.html",
    "json_url": "https://www.searchapi.io/api/v1/searches/search_AEM9arelpd2kFE2QoW0Nw8nB"
  },
  "search_parameters": {
    "engine": "google_scholar",
    "google_domain": "google.com",
    "hl": "en",
    "cites": "10342765531442280392"
  },
  "search_information": {
    "total_results": 135,
    "page": 1,
    "time_taken_displayed": 0.03
  },
  "organic_results": [
    {
      "position": 1,
      "title": "“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research …",
      "data_cid": "gt4k4ov5NCUJ",
      "link": "https://www.sciencedirect.com/science/article/pii/S0268401223000233",
      "publication": "YK Dwivedi, N Kshetri, L Hughes, EL Slade… - International Journal of …, 2023 - Elsevier",
      "snippet": "Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a …",
      "inline_links": {
        "cited_by": {
          "cites_id": "2681042057382125186",
          "total": 250,
          "link": "https://scholar.google.com/scholar?cites=2681042057382125186&as_sdt=2005&sciodt=0,5&hl=en"
        },
        "versions": {
          "cluster_id": "2681042057382125186",
          "total": 30,
          "link": "https://scholar.google.com/scholar?cluster=2681042057382125186&hl=en&as_sdt=2005&sciodt=0,5"
        },
        "related_articles_link": "https://scholar.google.com/scholar?q=related:gt4k4ov5NCUJ:scholar.google.com/&scioq=&hl=en&as_sdt=2005&sciodt=0,5"
      },
      "resource": {
        "name": "sciencedirect.com",
        "format": "HTML",
        "link": "https://www.sciencedirect.com/science/article/pii/S0268401223000233"
      },
      "authors": [
        {
          "name": "YK Dwivedi",
          "id": "SQ_uDYIAAAAJ",
          "link": "https://scholar.google.com/citations?user=SQ_uDYIAAAAJ&hl=en&oi=sra"
        },
        ...
      ]
    },
    ...
  ],
  "pagination": {
    "current": 1,
    "next": "https://scholar.google.com/scholar?start=10&hl=en&as_sdt=2005&sciodt=0,5&cites=10342765531442280392&scipsc=",
    "other_pages": [
      "https://scholar.google.com/scholar?start=10&hl=en&as_sdt=2005&sciodt=0,5&cites=10342765531442280392&scipsc=",
      ...
    ]
  }
}

Profiles

GET

https://www.searchapi.io/api/v1/search?engine=google_scholar&q=author%3AIlya+Sutskever

Request

import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_scholar",
  "q": "author:Ilya Sutskever"
}

response = requests.get(url, params=params)
print(response.text)

Response

{
  ...
  "profiles": [
    {
      "author_id": "x04W_mMAAAAJ",
      "name": "Ilya Sutskever",
      "link": "https://scholar.google.com/citations?user=x04W_mMAAAAJ&hl=en&oi=ao",
      "affiliations": "Co-Founder and Chief Scientist of OpenAI",
      "email": "Verified email at openai.com",
      "cited_by": {
        "total": 422635
      }
    }
  ]
  ...
}

GET

https://www.searchapi.io/api/v1/search?engine=google_scholar&q=AI

Request

import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_scholar",
  "q": "AI"
}

response = requests.get(url, params=params)
print(response.text)

Response

{
  ...
  "related_searches": [
    {
      "query": "mario ai championship",
      "highlighted": [
        "mario",
        "championship"
      ],
      "link": "https://scholar.google.com/scholar?hl=en&as_sdt=0,33&qsp=1&q=mario+ai+championship&qst=ir"
    },
    ...
  ],
  ...
}

Google Scholar API

API Parameters

Search Query

Localization

Filters

Engine

API key

API Examples

Full Response

Cluster Search

Cites Search

Profiles