# OpenAlex Scientific Papers & Citations Scraper — 250M+ Acade (`spotless_studios/openalex-research-scraper`) Actor

Scrape academic papers, scientific research studies, citation metrics, author institutions, open-access PDFs, and DOIs from OpenAlex. Global scholarly literature search and monitoring.

- **URL**: https://apify.com/spotless_studios/openalex-research-scraper.md
- **Developed by:** [Spotless Studios](https://apify.com/spotless_studios) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 scientific paper extracteds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## OpenAlex Scientific Papers & Citations Scraper

Harvest scholarly literature, research papers, citation metrics, author institutions, open-access PDFs, and DOIs from OpenAlex's index of 250M+ academic works.

### Features

- **Rich Scholarly Telemetry**: Extracts paper title, DOI, publication year, journal/conference source, citation count, open access PDF URL, authors, university affiliations, and reconstructed plain-text abstracts.
- **Granular Academic Filters**: Filter by research topic concepts, publication year ranges, minimum citation counts, open-access availability, and university/institution names.
- **Automated Research Monitoring**: Run on a schedule with `onlyNewItems` and `stateKey` to get alerts whenever groundbreaking papers matching your queries are published.
- **Lightweight & High Speed**: Direct JSON API queries with zero browser dependencies, consuming minimal Apify compute credits.

### Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `searchQuery` | String | `"large language models"` | Scientific topic, disease, technology, or title |
| `fromYear` | Integer | `null` | Earliest publication year (e.g. 2024) |
| `toYear` | Integer | `null` | Latest publication year (e.g. 2026) |
| `minCitations` | Integer | `0` | Minimum citation count threshold |
| `openAccessOnly` | Boolean | `false` | Restrict to open-access / free-to-read papers |
| `institutionName` | String | `""` | Filter by university or research institute |
| `sortBy` | String | `"cited_by_count:desc"` | `cited_by_count:desc`, `publication_date:desc`, `relevance_score:desc` |
| `maxResults` | Integer | `100` | Maximum papers to extract |
| `onlyNewItems` | Boolean | `false` | Monitoring mode: only emit newly published works |
| `outputPreset` | String | `"full"` | `full`, `lean`, or `contacts` |

### Output Example

```json
{
  "workId": "https://openalex.org/W4389021841",
  "doi": "https://doi.org/10.1038/s41586-024-00001-x",
  "title": "Scaling Autonomous Agents in Multi-Turn Reasoning Tasks",
  "publicationYear": 2025,
  "publicationDate": "2025-04-12",
  "type": "article",
  "citedByCount": 182,
  "authors": [
    { "name": "Elena Rostova", "id": "https://openalex.org/A5021", "institution": "Stanford University" }
  ],
  "primarySource": "Nature Machine Intelligence",
  "isOa": true,
  "oaUrl": "https://arxiv.org/pdf/2404.12345.pdf",
  "concepts": [
    { "name": "Artificial intelligence", "score": 0.88 },
    { "name": "Reinforcement learning", "score": 0.76 }
  ],
  "abstract": "We investigate how autonomous reasoning agents scale across iterative pair programming environments...",
  "scrapedAt": "2026-10-27T12:00:00.000Z"
}
```

***

### More from Spotless Studios

**[All actors on Apify](https://apify.com/spotless_studios)** · Support: spotless.studios.info@gmail.com

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|-------|----------|
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| [UK Planning Applications](https://apify.com/spotless_studios/uk-planning-applications-scraper) | UK planning leads + agent contacts |
| [Product Hunt](https://apify.com/spotless_studios/product-hunt-scraper) | Every PH launch + makers / websites |
| [Duunitori Jobs](https://apify.com/spotless_studios/duunitori-jobs-scraper) | Finland job listings |
| [Clutch Agencies](https://apify.com/spotless_studios/clutch-agencies-scraper) | Clutch agency prospecting |
| [Skool Communities](https://apify.com/spotless_studios/skool-communities-scraper) | Skool community & creator leads |

# Actor input Schema

## `searchQuery` (type: `string`):

Search title, abstract, and fulltext across 250M+ works (e.g. 'large language models', 'CRISPR gene editing', 'solid state battery').

## `searchQueries` (type: `array`):

Optional list of multiple research queries to run sequentially in a single job.

## `workType` (type: `string`):

Filter by scholarly work type.

## `fromYear` (type: `integer`):

Minimum publication year (e.g. 2023).

## `toYear` (type: `integer`):

Maximum publication year (e.g. 2026).

## `minCitations` (type: `integer`):

Only return works cited at least this many times.

## `openAccessOnly` (type: `boolean`):

When enabled, only returns works with free full-text Open Access links.

## `institutionName` (type: `string`):

Filter works by institution name (e.g. 'Stanford University', 'MIT', 'Oxford').

## `countryCode` (type: `string`):

Two-letter ISO country code of the author's institution (e.g. 'US', 'GB', 'DE', 'CH').

## `authorOrcid` (type: `string`):

Filter works by a specific author's ORCID (e.g. '0000-0002-1825-0097').

## `funderName` (type: `string`):

Keep only works funded by a matching agency (e.g. 'National Science Foundation', 'NIH', 'European Commission').

## `sortBy` (type: `string`):

Order results by citation count, publication date, or relevance.

## `workIds` (type: `array`):

Scrape specific works directly by DOI ('10.1038/s41586-021-03819-2') or OpenAlex ID ('W2741809807').

## `includeKeywords` (type: `array`):

Keep only papers matching these keywords or /regex/ in title, abstract, authors, or concepts.

## `excludeKeywords` (type: `array`):

Skip papers matching any of these keywords or /regex/.

## `keywordMatch` (type: `string`):

Require any or all includeKeywords to match.

## `onlyNewItems` (type: `boolean`):

Remember seen work IDs across runs and emit only newly discovered publications.

## `stateKey` (type: `string`):

Separate state key per saved search or schedule.

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

Maximum number of scholarly works to save.

## `outputPreset` (type: `string`):

Choose full record, lean summary, or contacts & links only.

## `outputFields` (type: `array`):

Keep only these specific fields in each saved record.

## `excludeFields` (type: `array`):

Remove specific fields from each saved record.

## `includeEmptyFields` (type: `boolean`):

When disabled, strips null and empty values from each saved record.

## `requiredFields` (type: `array`):

Only save records where every listed field has a non-empty value (e.g. pdfUrl, abstract).

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

Maximum search pages per query (100 works per page).

## `maxConcurrency` (type: `integer`):

Parallel requests when fetching direct DOIs or work IDs.

## `maxRequestRetries` (type: `integer`):

Retries per failed HTTP request.

## `requestTimeoutSecs` (type: `integer`):

Timeout per HTTP request.

## `proxyConfiguration` (type: `object`):

Optional proxy settings.

## `proxyEscalation` (type: `boolean`):

Automatically step up from direct to Apify datacenter/residential proxies if blocked.

## Actor input object example

```json
{
  "searchQuery": "large language models",
  "workType": "all",
  "openAccessOnly": false,
  "sortBy": "cited_by_count:desc",
  "keywordMatch": "any",
  "onlyNewItems": false,
  "stateKey": "default",
  "maxResults": 50,
  "outputPreset": "full",
  "includeEmptyFields": true,
  "maxPages": 15,
  "maxConcurrency": 5,
  "maxRequestRetries": 3,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  },
  "proxyEscalation": true
}
```

# Actor output Schema

## `items` (type: `string`):

Scrape academic papers, scientific research studies, citation metrics, author institutions, open-access PDFs, and DOIs from OpenAlex. Global scholarly literature search and monitoring.

# 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 = {
    "searchQuery": "large language models",
    "maxResults": 50,
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("spotless_studios/openalex-research-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 = {
    "searchQuery": "large language models",
    "maxResults": 50,
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("spotless_studios/openalex-research-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 '{
  "searchQuery": "large language models",
  "maxResults": 50,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call spotless_studios/openalex-research-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,spotless_studios/openalex-research-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/tn8qwnI4cIceoehoh/builds/09Z2qtlBkecieFlLE/openapi.json