# Google Scholar Scraper (`thescrappa/google-scholar-scraper`) Actor

Search Google Scholar for paper titles, authors, publication details, citations, and available resources. Batch research queries to build literature lists or monitor academic topics.

- **URL**: https://apify.com/thescrappa/google-scholar-scraper.md
- **Developed by:** [Scrappa](https://apify.com/thescrappa) (community)
- **Categories:** Education, SEO tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.20 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Google Scholar Scraper

Collect ranked Scholar results for research topics. Rows include paper titles, result IDs, publication summaries, snippets, links, and available resources.

### What data can you extract?

| Field | Type | Description |
| --- | --- | --- |
| `position` | Integer | Position of the paper in Google Scholar results, starting at 1. |
| `title` | String | Paper title displayed by Google Scholar. |
| `result_id` | String | Google Scholar identifier associated with the paper record. |
| `link` | String | Google Scholar or publisher URL for the paper. |
| `snippet` | String | Short paper excerpt or matching text shown in Scholar results. |
| `publication_info` | Object | Publication venue, authors, and year displayed with the paper. |
| `resources` | Array\<object> | Publisher and document links associated with the paper. |
| `input_q` | String | Research phrase submitted to Google Scholar for this result set. |
| `scraped_at` | String | UTC date and time when this paper record was collected. |

### Use cases

- Researchers can collect paper details and publisher links by topic.
- Librarians can build reading lists from ranked Google Scholar results.
- Research teams can monitor publication coverage for recurring queries.

### How to use

1. Add one research phrase per item in `queries`.
2. Set `maxPages` to bound collection and `maxResults` to cap saved papers.
3. Review paper titles, publication details, links, and resources.

```json
{
  "queries": [
    {
      "q": "transformer attention"
    }
  ],
  "maxResults": 20,
  "maxPages": 2
}
```

### Input

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| `queries` | Array\<object> | Yes | Academic search phrases. Add one object per phrase. |
| `queries[].q` | string | Yes per entry | Scholar search query. Optional when cites or cluster is supplied. |
| `queries[].hl` | string | No | Two-letter interface language, optionally with a region. Defaults to en. |
| `queries[].start` | integer | No | Zero-based result offset from 0 to 990. Defaults to 0. |
| `queries[].num` | integer | No | Results per request from 1 to 20. Defaults to 10. |
| `queries[].as_ylo` | integer | No | Earliest publication year to include. |
| `queries[].as_yhi` | integer | No | Latest publication year to include. |
| `queries[].scisbd` | integer | No | 0 for relevance, 1 for recent abstracts, or 2 for all recent additions. Allowed values: 0, 1, 2. |
| `queries[].cites` | string | No | Numeric publication ID for a cited-by search. May be combined with q. |
| `queries[].cluster` | string | No | Numeric publication ID for an all-versions search. Must be used alone. |
| `hl` | string | No | Two-letter interface language, optionally with a region. Defaults to en. |
| `start` | integer | No | Zero-based result offset from 0 to 990. Defaults to 0. |
| `num` | integer | No | Results per request from 1 to 20. Defaults to 10. |
| `as_ylo` | integer | No | Earliest publication year to include. |
| `as_yhi` | integer | No | Latest publication year to include. |
| `scisbd` | integer | No | 0 for relevance, 1 for recent abstracts, or 2 for all recent additions. Allowed values: 0, 1, 2. |
| `cites` | string | No | Numeric publication ID for a cited-by search. May be combined with q. |
| `cluster` | string | No | Numeric publication ID for an all-versions search. Must be used alone. |
| `maxResults` | integer | No | Maximum dataset items to save across this entire run. |
| `maxPages` | integer | No | Maximum pages to request for each batch entry. |

### Output example

```json
{
  "position": 1,
  "title": "How Search Interfaces Shape Literature Reviews",
  "result_id": "GS-2025-01842",
  "link": "https://scholar.google.com/scholar?cluster=1748293102842",
  "snippet": "This study compares citation discovery and screening workflows across digital research libraries.",
  "publication_info": {
    "summary": "Journal of Digital Scholarship, 2025",
    "authors": [
      "Priya Menon",
      "Rafael Costa"
    ]
  },
  "resources": [
    {
      "title": "Open access article",
      "file_format": "PDF",
      "link": "https://repository.uni-muenster.de/document/1842"
    }
  ],
  "input_q": "transformer attention",
  "scraped_at": "2026-10-01T12:00:00Z"
}
```

### Pricing

$0.30 per 1,000 results. Apify saves one dataset item per result and applies the Actor’s per-result price to saved items.

Pagination follows the source response. Set **maxPages** per batch entry and **maxResults** across the run.

### FAQ

#### Is scraping this information legal?

Rules depend on the source, location, data type, and intended use. Check applicable laws and source terms, and make sure your workflow follows privacy and data protection requirements.

#### What limits apply?

Submit up to 100 batch entries per run. Use **maxResults** to cap saved items and **maxPages** to limit pages for each entry. Results also depend on source availability and your Scrappa API plan.

#### Can I start runs through the Apify API?

Yes. Send a POST request to `https://api.apify.com/v2/acts/thescrappa~google-scholar-scraper/runs` with your Actor input, or use an Apify client library. Read the output from the run dataset.

#### Can I connect the results to other tools?

Yes. Apify integrations and APIs can pass dataset results to Make, Zapier, n8n, Google Sheets, and other data workflows.

#### What happens when one input fails?

The Actor logs a short source error and continues with the remaining entries. Transient rate limits and gateway errors are retried; if every entry fails, the run reports an error.

#### Does the Actor download full papers?

No. It returns result metadata and resource links exposed in search results; publisher access rules still apply.

### Related Scrappa Actors

- [Google AI Overview Scraper](https://apify.com/thescrappa/google-ai-overview-scraper)
- [Bing Search Scraper](https://apify.com/thescrappa/bing-search-scraper)
- [Google Shopping Scraper](https://apify.com/thescrappa/google-shopping-scraper)

# Actor input Schema

## `queries` (type: `array`):

Academic search phrases. Add one object per phrase.

## `hl` (type: `string`):

Two-letter interface language, optionally with a region. Defaults to en.

## `start` (type: `integer`):

Zero-based result offset from 0 to 990. Defaults to 0.

## `num` (type: `integer`):

Results per request from 1 to 20. Defaults to 10.

## `as_ylo` (type: `integer`):

Earliest publication year to include.

## `as_yhi` (type: `integer`):

Latest publication year to include.

## `scisbd` (type: `integer`):

0 for relevance, 1 for recent abstracts, or 2 for all recent additions. Allowed values: 0, 1, 2.

## `cites` (type: `string`):

Numeric publication ID for a cited-by search. May be combined with q.

## `cluster` (type: `string`):

Numeric publication ID for an all-versions search. Must be used alone.

## `maxResults` (type: `integer`):

Maximum dataset items to save across this entire run.

## `maxPages` (type: `integer`):

Maximum pages to request for each batch entry.

## Actor input object example

```json
{
  "queries": [
    {
      "q": "transformer attention"
    }
  ],
  "hl": "en",
  "start": 0,
  "num": 10,
  "scisbd": 0,
  "maxResults": 20,
  "maxPages": 2
}
```

# Actor output Schema

## `results` (type: `string`):

All results from this run in the default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        {
            "q": "transformer attention"
        }
    ],
    "maxResults": 20,
    "maxPages": 2
};

// Run the Actor and wait for it to finish
const run = await client.actor("thescrappa/google-scholar-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queries": [{ "q": "transformer attention" }],
    "maxResults": 20,
    "maxPages": 2,
}

# Run the Actor and wait for it to finish
run = client.actor("thescrappa/google-scholar-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    {
      "q": "transformer attention"
    }
  ],
  "maxResults": 20,
  "maxPages": 2
}' |
apify call thescrappa/google-scholar-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thescrappa/google-scholar-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/TVRMwvlFCXKSKMUpk/builds/HP9R3xba5sbJ5QQf8/openapi.json