# OpenAlex — Academic Papers & Citations Search (`omao/openalex`) Actor

Search 250M+ scholarly works via OpenAlex into clean JSON: title, authors, venue, year, citation count, open-access status, PDF URL, concepts and reconstructed abstract. Powered by the public OpenAlex API. No API key.

- **URL**: https://apify.com/omao/openalex.md
- **Developed by:** [Marouane Oulabass](https://apify.com/omao) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 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/platform/actors/running/actors-in-store#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 — Academic Papers & Citations Search to JSON

**Search hundreds of millions of scholarly works via OpenAlex — as clean JSON.** Pass topics, titles or keywords and get back a tidy row per paper: title, authors, venue, year, citation count, open-access status, PDF URL, concepts and a reconstructed abstract. Powered by the public OpenAlex API — no API key.

The easy way to build research and citation datasets for science, RAG and analytics.

### Who uses this

- 🎓 **Researchers & academics** — find papers and track citations on any topic.
- 🤖 **AI / LLM & RAG pipelines** — ingest abstracts and metadata at scale.
- 📊 **Research analysts & librarians** — study venues, citations and open access.
- 🏢 **R\&D & competitive intel** — monitor publications in your field.
- 🧑‍💻 **Developers** — a clean scholarly-search endpoint by keyword.

### What you get — one clean row per paper

| Field | Description |
|---|---|
| `title` | Paper title |
| `authors` + `authorCount` | Authors |
| `venue` | Journal / venue |
| `publicationYear` + `publicationDate` | Publication date |
| `citedByCount` | Citation count |
| `isOpenAccess` + `oaUrl` | Open-access status & URL |
| `concepts` | Topics / concepts |
| `abstract` | Reconstructed abstract |
| `doi` + `pmid` | External IDs |
| `referencedWorksCount` | References count |
| `landingPageUrl` + `pdfUrl` | Links |

### Example

**Input**

```json
{ "queries": ["large language models", "crispr gene editing"], "maxResultsPerQuery": 25 }
```

**Output (one item)**

```json
{
  "id": "https://openalex.org/W2741809807",
  "title": "Attention Is All You Need",
  "authors": ["Ashish Vaswani", "Noam Shazeer"],
  "venue": "NeurIPS", "publicationYear": 2017,
  "citedByCount": 95000, "isOpenAccess": true,
  "concepts": ["Artificial intelligence", "Transformer"],
  "doi": "https://doi.org/10.5555/3295222.3295349"
}
```

### Why this actor

- ✅ **Massive coverage** — OpenAlex indexes 250M+ scholarly works.
- 🔎 **Keyword search** — topics, titles and terms.
- 📈 **Citation counts** — measure impact per paper.
- 📝 **Reconstructed abstracts** — full abstract text, ready for LLM/RAG.
- ⚡ **Fast & affordable** — pay only per paper returned. No API key.

### Input options

- `queries` *(required)* — academic search queries.
- `maxResultsPerQuery` — cap papers per query.

### FAQ

**Do I get the abstract?** Yes — the abstract is reconstructed from OpenAlex's inverted index into readable text.

**Are citation counts included?** Yes — `citedByCount` per paper.

**Can I find open-access PDFs?** Yes — `isOpenAccess` and `oaUrl`/`pdfUrl` when available.

**How fresh is the data?** Live from the OpenAlex API on every run.

**Can I export to CSV/Excel/Google Sheets?** Yes — the dataset exports to JSON, CSV, Excel and HTML, or pull it via the API.

**What does it cost?** Pay-per-paper — you're only charged for papers actually returned.

***

*Tip: search your field's key terms and sort your dataset by `citedByCount` to find the most influential papers.*

# Actor input Schema

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

Academic search queries (topic, title, keyword). One search per query.

## `maxResultsPerQuery` (type: `integer`):

Cap the number of papers per query.

## `healthCheckMode` (type: `boolean`):

Internal monitoring: run a canary search and FAIL if broken (no billing).

## Actor input object example

```json
{
  "queries": [
    "crispr gene editing",
    "large language models"
  ],
  "maxResultsPerQuery": 25,
  "healthCheckMode": false
}
```

# Actor output Schema

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

All papers (title, authors, venue, citations, open access, abstract).

# 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": [
        "machine learning"
    ]
};

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

# Run the Actor and wait for it to finish
run = client.actor("omao/openalex").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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": [
    "machine learning"
  ]
}' |
apify call omao/openalex --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=omao/openalex",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/bspQhaTELVDPqvkdd/builds/8rxuBBqrJ4h6cgSbh/openapi.json