# Research Papers Search (OpenAlex, 250M+ works) (`ninja.dev/research-papers-openalex`) Actor

Search 250M+ scholarly papers by topic or look up DOIs. Returns title, abstract, authors with institutions, venue, year, citation count, open-access PDF link, topics and funders. Filter by year, citations, open access and type. Data from OpenAlex, covering PubMed, arXiv and Crossref.

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

## Pricing

from $1.00 / 1,000 papers

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

## Research Papers Search (OpenAlex, 250M+ works)

Search the world's scholarly literature and get clean, structured records, ready for a literature review, a spreadsheet or an AI research agent.

Powered by **OpenAlex**, the open catalog of 250M+ scholarly works that includes PubMed, arXiv, Crossref and institutional repositories. No API key, no login.

### What you get per paper

Title, **abstract**, year and date, type (article, review, preprint...), DOI and PubMed ID, venue and publisher, **citation count** and citation percentile, **open-access status and PDF link**, **authors with institutions, countries and ORCID**, primary topic, field and domain, keywords, funders, number of references and retraction flag.

### Use cases

- **Literature reviews**: the most relevant or most cited papers on a topic, with abstracts.
- **AI research agents**: grounded citations with DOIs and open PDFs instead of hallucinated references.
- **Find experts**: authors and institutions publishing on a topic.
- **Track a field**: newest preprints on a topic with a scheduled run.
- **Enrich a reference list**: pass DOIs and get full metadata.

### Input

| Field | What it does |
|---|---|
| `searchQueries` | Topics, e.g. `CRISPR off-target effects`. |
| `dois` | Specific papers to look up. |
| `maxResultsPerQuery` | Default 25, up to 2,000. |
| `sortBy` | `relevance` (default), `citations` or `newest`. |
| `yearFrom` / `yearTo` | Publication year range. |
| `minCitations` | Skip papers cited fewer times. |
| `openAccessOnly` | Only free-to-read papers. |
| `types` | `article`, `review`, `preprint`, `book-chapter`, `dataset`... |
| `excludeRetracted` | Default on. |

Tip: sorting by `citations` without a year filter surfaces famous but loosely related papers; combine it with `yearFrom` for "most cited recent work on X".

### Output

```json
{
  "recordType": "paper",
  "title": "Array programming with NumPy",
  "year": 2020,
  "type": "article",
  "doi": "https://doi.org/10.1038/s41586-020-2649-2",
  "venue": "Nature",
  "citedBy": 23182,
  "isOpenAccess": true,
  "pdfUrl": "https://www.nature.com/articles/s41586-020-2649-2.pdf",
  "authors": [{ "name": "Charles R. Harris", "institutions": [], "orcid": null }],
  "authorCount": 26,
  "abstract": "Array programming provides a powerful, compact and expressive syntax ...",
  "primaryTopic": { "topic": "...", "field": "Computer Science", "domain": "Physical Sciences" }
}
```

Errors (unknown DOI, no results, bad filter) come back as `recordType: "error"` rows with a `hint`.

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- [SEC EDGAR Filings & Financials](https://apify.com/ninja.dev/sec-edgar-filings-financials): SEC filings and normalized financials.
- [Telegram Channel Scraper](https://apify.com/ninja.dev/telegram-channel-scraper): public Telegram channel posts, with monitor mode.

# Actor input Schema

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

Topics to search in titles, abstracts and full text, e.g. CRISPR off-target effects.

## `dois` (type: `array`):

Look up specific papers, e.g. 10.1038/s41586-020-2649-2 or https://doi.org/...

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

Maximum papers returned for each query.

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

Relevance works best for topic searches; use citations together with a year filter.

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

Only papers published in or after this year.

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

Only papers published in or before this year.

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

Skip papers cited fewer times than this.

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

Only papers that are free to read.

## `types` (type: `array`):

Optional: article, review, preprint, book-chapter, dataset, dissertation.

## `excludeRetracted` (type: `boolean`):

Skip papers flagged as retracted.

## Actor input object example

```json
{
  "searchQueries": [
    "large language model agents"
  ],
  "maxResultsPerQuery": 25,
  "sortBy": "relevance",
  "openAccessOnly": false,
  "excludeRetracted": true
}
```

# Actor output Schema

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

Papers with title, abstract, authors and institutions, venue, citations, open-access PDF, topics and funders.

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

Number of papers and the list of issues.

# 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 model agents"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("ninja.dev/research-papers-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 = { "searchQueries": ["large language model agents"] }

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

```

## MCP server setup

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

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/XAm7IGd8zVRJ5iqaS/builds/YZzVOIUVwTCng9Ae2/openapi.json