# OpenAlex Scraper | Scholarly Papers, Citations & Abstracts (`muzafferkadir/openalex-scraper`) Actor

Scrape scholarly works from OpenAlex by keyword, date, type and open-access status: title, authors, citations, venue, topics and abstract. Official API, no API key.

- **URL**: https://apify.com/muzafferkadir/openalex-scraper.md
- **Developed by:** [Muzaffer Kadir YILMAZ](https://apify.com/muzafferkadir) (community)
- **Categories:** Education, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 works

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 Scraper

Scrape **scholarly works** from **OpenAlex** by keyword, date, type, and open-access status — **title, authors, institutions, citations, venue, topics, open-access links, and a reconstructed abstract**. Built on the **official OpenAlex API**: over 250M works across every field, no API key or setup needed.

Search a topic like `large language models`, get a clean, dated, analysis-ready list of matching papers — ready to export to CSV, Excel, or JSON, or to power a research-monitoring pipeline.

### Features

- **Official, reliable source** — reads the public OpenAlex API.
- **Full scholarly metadata** — citations, authors, institutions, venue, topics, DOI, and open-access URLs in one clean row.
- **Real abstracts** — OpenAlex stores abstracts as an inverted index; this Actor reconstructs them into readable text.
- **Monitoring-ready** — schedule it on your topics and catch new papers as they're indexed.

### Use cases

- **Literature review & discovery** — researchers and students tracking a field.
- **Citation & impact analysis** — build datasets of citations by topic, venue, or institution.
- **Research monitoring** — schedule daily and flag new papers on your keywords.
- **Open-access tracking** — filter to open-access works and collect direct PDF/landing links.

### Input

| Field | Type | Description |
| --- | --- | --- |
| `searchQueries` | string\[] | Topics or keywords. Leave empty to list the most recent works. |
| `fromDate` | string | Only works published on/after this `YYYY-MM-DD` date. |
| `type` | enum | Work type: `article`, `preprint`, `book-chapter`, `dataset`, `review`. |
| `openAccessOnly` | boolean | Only open-access works. |
| `maxItems` | integer | Max works per query. Default 100. |

#### Example

```json
{
  "searchQueries": ["large language models"],
  "fromDate": "2025-01-01",
  "type": "article",
  "openAccessOnly": true,
  "maxItems": 100
}
```

### Output

```json
{
  "openalexId": "W4401234567",
  "doi": "https://doi.org/10.1234/example",
  "title": "Scaling Laws for Large Language Models",
  "year": 2025,
  "publicationDate": "2025-03-14",
  "citedByCount": 42,
  "type": "article",
  "authors": ["Jane Doe", "John Smith"],
  "institutions": ["Stanford University", "MIT"],
  "venue": "Nature Machine Intelligence",
  "isOpenAccess": true,
  "oaUrl": "https://example.org/paper.pdf",
  "topics": ["Machine Learning", "Natural Language Processing"],
  "referencedWorksCount": 58,
  "abstract": "We study how model performance scales with...",
  "url": "https://openalex.org/W4401234567",
  "query": "large language models",
  "scrapedAt": "2026-08-11T19:00:00.000Z"
}
```

Download the dataset as **JSON, CSV, Excel, or XML**, or pull it via the Apify API.

### Pricing

Pay-per-event: **$0.01 per run start** (per GB of run memory) plus **$0.50 per 1,000 works**. You only pay for works actually returned. See the **Pricing** tab for current rates.

### FAQ

**Do I need an API key?**
No. OpenAlex is a free, open catalog of scholarly works; this Actor packages its API into clean, filtered rows.

**Where do abstracts come from?**
OpenAlex stores abstracts as an inverted word index. This Actor rebuilds the original readable text from that index (capped for length).

**Can I list recent papers without a keyword?**
Yes — leave `searchQueries` empty and use `fromDate`, `type`, or `openAccessOnly` to filter.

**Can I monitor a field?**
Yes — schedule the Actor (e.g. daily) with your topics and a recent `fromDate`.

### Disclaimer

This Actor uses the **public OpenAlex API**. It is not affiliated with or endorsed by OpenAlex or OurResearch. The data is public; you are responsible for how you use it.

# Actor input Schema

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

Topics or keywords to search across 250M+ scholarly works, e.g. "large language models", "crispr". Leave empty to list the most recent works.

## `fromDate` (type: `string`):

Only include works published on or after this date, in YYYY-MM-DD format. Leave empty for no lower bound.

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

Filter works by type. Leave as Any to include all types.

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

When enabled, only open-access works are returned.

## `maxItems` (type: `integer`):

Stop after collecting this many works for each search query.

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

Optional. Leave empty for most runs.

## Actor input object example

```json
{
  "searchQueries": [
    "large language models"
  ],
  "type": "",
  "openAccessOnly": false,
  "maxItems": 100
}
```

# Actor output Schema

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

No description

# 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 = {
    "searchQueries": [
        "large language models"
    ],
    "maxItems": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("muzafferkadir/openalex-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 = {
    "searchQueries": ["large language models"],
    "maxItems": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("muzafferkadir/openalex-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 '{
  "searchQueries": [
    "large language models"
  ],
  "maxItems": 100
}' |
apify call muzafferkadir/openalex-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,muzafferkadir/openalex-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/bbPxOiKue5g1DaQP8/builds/puZBVaMMMva9xTwly/openapi.json