# OpenAlex Academic Research Scraper (`cynix_dev/openalex-research`) Actor

Search 250M+ scholarly works, authors, institutions, and concepts from the OpenAlex API. Get titles, authors, citations, open access status, PDFs, and concepts. No API key required.

- **URL**: https://apify.com/cynix_dev/openalex-research.md
- **Developed by:** [Cynix Dev](https://apify.com/cynix_dev) (community)
- **Features:** Limited permissions
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $54.00 / 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

## OpenAlex Academic Research Scraper

Search **250M+ scholarly works, authors, institutions, and concepts** from the
[OpenAlex](https://openalex.org) database. No API key required.

![OpenAlex](https://img.logo.dev/openalex.org?token=pk_f3e1270e3c2e4cb5a0c3a8d86e96b90a\&size=200\&retina=true\&format=png)

### What it does

This actor queries the [OpenAlex API](https://docs.openalex.org/) — the fully
open replacement for Microsoft Academic Graph and a complement to Scopus/Web of
Science — and returns structured rows for any entity:

- **Works**: research papers with title, authors, journal, DOI, citations, concepts, open-access PDF
- **Authors**: scholars with institutional affiliation and citation counts
- **Institutions**: universities/research orgs with publication output
- **Concepts**: research topics with publication counts

### Example Inputs

#### Search for most-cited LLM papers

```json
{
  "mode": "search",
  "entityType": "works",
  "searchQuery": "large language model",
  "maxResults": 25,
  "sortBy": "cited_by_count:desc"
}
```

#### Recent CRISPR papers in a date range

```json
{
  "mode": "search",
  "entityType": "works",
  "searchQuery": "crispr gene editing",
  "yearFrom": 2022,
  "yearTo": 2024,
  "maxResults": 50,
  "sortBy": "publication_date:desc"
}
```

#### Get a specific paper by OpenAlex ID

```json
{
  "mode": "workId",
  "entityType": "works",
  "workId": "W2741809807"
}
```

#### Find an institution's publication profile

```json
{
  "mode": "search",
  "entityType": "institutions",
  "searchQuery": "MIT Massachusetts Institute of Technology",
  "maxResults": 5
}
```

### Output

Each record contains:

| Field | Description |
|-------|-------------|
| `entity_type` | works / authors / institutions / concepts |
| `id` | Canonical OpenAlex ID |
| `display_name` | Title or entity name |
| `publication_year` | Year published |
| `cited_by_count` | Citation count |
| `doi` | Digital Object Identifier |
| `type` | Document type or entity subtype |
| `authors` | Semicolon-separated author names |
| `journal` | Journal/venue or affiliation |
| `open_access` | Open Access status (gold, green, hybrid) |
| `pdf_url` | Link to open-access full text |
| `concepts` | Semicolon-separated research topics |

### Data Source

[OpenAlex](https://openalex.org) — a fully open catalog of global scholarly
research, released under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)
(public domain). Covers 250M+ works from 1960 to present.

### Use Cases

- **Literature reviews**: find highly-cited papers on any topic
- **Citation analysis**: track influence and impact of research
- **Academic prospecting**: identify top authors in a field
- **Institution benchmarking**: compare research output across universities
- **RAG / knowledge bases**: feed structured research metadata into AI pipelines
- **Pharma / biotech**: discover clinical-relevant literature

### Rate Limits

OpenAlex requests clients to keep requests under 10/second. This actor respects
that with a built-in 150ms delay between page requests. For large paginated
searches it pauses gracefully on 429 responses.

### Limitations

- Coverage is strongest 1996-present, with full-text backfill earlier
- Some works lack author disambiguation (merged author records)
- `cited_by_count` reflects OpenAlex's citation index, not Scopus/WoS

# Actor input Schema

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

What type of entity to search for. 'search' uses keyword search; 'title' filters by exact title match; 'workId' fetches a single work by OpenAlex ID.

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

Which OpenAlex entity collection to query.

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

Search term for keyword mode. E.g. 'transformer architecture', 'crispr gene editing'.

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

OpenAlex work identifier (e.g. W2741809807 or https://openalex.org/W2741809807). Used when mode is 'workId'.

## `yearFrom` (type: `integer`):

Filter results published in or after this year (0 = no filter).

## `yearTo` (type: `integer`):

Filter results published in or before this year (0 = no filter).

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

Maximum number of results to return (max 200 per page, paginated).

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

Field to sort results by. Use ':asc' or ':desc' suffix. Defaults to relevance (no sort).

## Actor input object example

```json
{
  "mode": "search",
  "entityType": "works",
  "searchQuery": "large language model",
  "workId": "",
  "yearFrom": 0,
  "yearTo": 0,
  "maxResults": 25,
  "sortBy": "cited_by_count:desc"
}
```

# Actor output Schema

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

Dataset containing all scraped records

# 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 model"
};

// Run the Actor and wait for it to finish
const run = await client.actor("cynix_dev/openalex-research").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 model" }

# Run the Actor and wait for it to finish
run = client.actor("cynix_dev/openalex-research").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 model"
}' |
apify call cynix_dev/openalex-research --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,cynix_dev/openalex-research"
        }
    }
}
```

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/qtiTNPNkFov8Mma8a/builds/e1B8RJ3Kt3bflehAZ/openapi.json