# OpenAlex Scraper - Scholarly Works & Citations (`scrapesage/openalex-scraper`) Actor

Scrape scholarly works from OpenAlex (250M+ papers): title, DOI, authors, institutions, journal/venue, year, citation count, open-access status, topics and PDF link. Search any topic. No key, no browser.

- **URL**: https://apify.com/scrapesage/openalex-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** Agents, Integrations, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.10 / 1,000 work scrapeds

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## OpenAlex Scraper - Scholarly Works & Citations

Search **OpenAlex** - an open catalog of **250M+ scholarly works** - and get clean rows for every paper:
**title**, **DOI**, **authors**, **institutions**, **venue/journal**, **year**, **citation count**,
**open-access status**, **topics** and a **PDF link** where available. Search any topic, or use OpenAlex
filter syntax. Built on the official API - no key, no browser.

### What you get per work

| Field | Meaning |
|---|---|
| `title` / `doi` / `openAlexUrl` | Title, DOI, and the OpenAlex record |
| `authors` / `authorCount` / `institutions` | Authors and their institutions |
| `venue` / `venueType` | Journal / repository / conference |
| `publicationYear` / `publicationDate` / `workType` | Dates and type (article, preprint, dataset…) |
| `citedByCount` / `referencedWorksCount` | Citations received and references made |
| `isOpenAccess` / `oaStatus` / `pdfUrl` | Open-access status and free full-text link |
| `topics` / `language` | Concepts/topics and language |

### Input

```json
{ "searchQueries": ["machine learning"], "sortBy": "cited", "maxItemsPerQuery": 100 }
```

- **Search queries** - one per line (searches titles, abstracts and full text).
- **Filter** - or use an OpenAlex filter expression, e.g. `publication_year:2024,is_oa:true`.
- **Import from a file** - paste a list, or link a public `.txt`/`.csv`, a Google Sheet/Drive link, or an
  Apify key-value-store record.
- **Sort by** relevance, most cited, or newest. **Max works** bound the run. **Output fields** trim it.

Leave everything empty and the run returns a small free sample so you can see the shape first.

### Reliability

Reads the official [OpenAlex API](https://docs.openalex.org/) - public, no key, no proxy, no anti-bot,
cursor-paginated for deep result sets. A run that returns nothing bills **$0**.

### Honest limits

- **Metadata and links, not full text.** You get the record and (for open-access works) a `pdfUrl`;
  closed-access works have a `landingPageUrl` at the publisher instead.
- **`pdfUrl` is present only for open-access works** - it reflects the work's OA status, not a scraping gap.

### Pricing

**$0.002 per work** on the FREE tier (tiered pricing lowers it with volume). Only works actually saved are
billed; an empty run costs nothing.

### Output views

- **Works** - title, authors, venue, year, citations, OA status, DOI and the PDF link.

### Use with AI assistants (MCP)

Available through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - an agent can
pull the most-cited or newest works on a topic (with DOIs and citation counts) for a review or a RAG index.

### Agent-ready: autonomous payments (x402 & Skyfire)

This actor is **agent-ready** - AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards:

- **[x402](https://docs.apify.com/platform/integrations/x402)** - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - no account, no API key.
- **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

# Actor input Schema

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

What to search OpenAlex for, one per line - e.g. <code>machine learning</code>, <code>gene therapy</code>. Searches titles, abstracts and full text. <b>Leave empty and the run returns a small free sample.</b>

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

An OpenAlex filter expression instead of / in addition to a search - e.g. <code>publication\_year:2024,is\_oa:true</code> or <code>authorships.institutions.country\_code:us</code>. See the OpenAlex docs.

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

Bulk-load search queries. Either <b>paste the whole list</b> (one per line), or give <b>a single link</b> to a public <code>.txt</code>/<code>.csv</code>, a Google Sheet/Drive link, or an Apify key-value-store record. A file that cannot be read says so and charges nothing.

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

How to order results.

## `maxItemsPerQuery` (type: `integer`):

How many works to collect for each search query.

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

Overall cap across all queries. You are only charged for works actually saved.

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

Pick the fields you want and every record is trimmed to exactly those - handy for lean CSV/Sheets exports.

## Actor input object example

```json
{
  "searchQueries": [
    "machine learning"
  ],
  "sortBy": "relevance",
  "maxItemsPerQuery": 50,
  "maxItems": 1000
}
```

# Actor output Schema

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

Each scraped record - scholarly works - as a JSON item 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 = {
    "searchQueries": [
        "machine learning"
    ],
    "searchQueriesFromFile": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/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": ["machine learning"],
    "searchQueriesFromFile": "",
}

# Run the Actor and wait for it to finish
run = client.actor("scrapesage/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": [
    "machine learning"
  ],
  "searchQueriesFromFile": ""
}' |
apify call scrapesage/openalex-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesage/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/s1omuKzJomcO62C8y/builds/Sn25o0hRv2XPtLgzW/openapi.json