# OpenAlex Scholarly Works Scraper: Papers, Citations, Abstracts (`tidyharvest/openalex-papers-scraper`) Actor

Search 250M+ research papers in OpenAlex: many keyword searches per run, or by author, institution or DOI. Authors with ORCID and affiliations, venue, citations, open-access PDF links, topics and full abstracts. No API key or proxy. $0.80 per 1,000 works.

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

## Pricing

from $0.48 / 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?

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 Scholarly Works Scraper: Papers, Citations, Abstracts

Search **250 million+ research papers, preprints, books and datasets** from **OpenAlex**, the open catalog of the global research system, and get clean rows with **title, DOI, authors with ORCID and affiliations, journal/venue, ISSN, citation counts, open-access PDF links, license, topics, keywords and the full abstract.** Every field of science, every publisher, not just preprint servers.

**$0.80 per 1,000 works.** No login, no proxy, no API key needed for normal runs. It reads the official OpenAlex API, so it is fast (about 100 works per second of API time) and stable.

### What you can do with it

- **Literature reviews and systematic searches:** pull every paper on a topic with year, type, open-access and citation filters, then screen in a spreadsheet.
- **Citation and impact analysis:** rank papers by citations or field-weighted citation impact (FWCI) for a topic, author or institution.
- **Research intelligence and lead lists:** find who publishes on a topic, with ORCID, institution and country for every author.
- **Open-access PDF harvesting:** get OA links and PDF URLs for papers that are free to read.
- **DOI enrichment:** paste a list of DOIs and get full metadata, abstracts and citation counts back.
- **AI and RAG pipelines:** feed titles and abstracts into embeddings, classifiers or LLM agents.

### How to use

1. Type one or more **search queries**, one per line (or an **author**, an **institution**, or a list of **DOIs**).
2. Optionally add filters: years, work type, open access only, minimum citations, language, sort order.
3. Click **Start** and download the results as JSON, CSV, Excel, or pull them through the Apify API.

### Input

| Field | What it does |
|---|---|
| `queries` | Searches to run, one per line (e.g. a topic list for a literature review). Supports `AND`, `OR`, `NOT` and "exact phrases". Each result says which search found it (`searchQuery`); a work found by two searches is returned once. |
| `query` | One search (same as one line of `queries`; kept for existing API callers). |
| `searchIn` | Title and abstract (default), title only, or full text too. |
| `dois` | List of DOIs to look up. When set, returns exactly these works. |
| `authorName` | Author name, ORCID or OpenAlex author id. Applies to every search. |
| `institutionName` | Institution name, ROR id or OpenAlex institution id. |
| `yearFrom` / `yearTo` | Publication year range. |
| `type` | Article, preprint, review, book, chapter, conference paper, dataset, dissertation... |
| `openAccessOnly` | Only works that are free to read. |
| `minCitations` | Only works cited at least N times. |
| `language` | Two-letter code, e.g. `en`. |
| `sortBy` | `relevance`, `citations` (most cited) or `date` (newest). |
| `includeAbstract` | Adds the abstract (default on). |
| `excludeRetracted` | Skips retracted works (default on). |
| `maxItems` | Cap on results per search (default 50, max 10,000). Set a maximum charge per run for a hard total. |
| `apiKey` | Optional free OpenAlex key for big or frequent runs (see Limits). |

Example:

```json
{
  "queries": ["perovskite solar cells", "tandem solar cells stability"],
  "yearFrom": 2022,
  "openAccessOnly": true,
  "minCitations": 50,
  "sortBy": "citations",
  "maxItems": 200
}
```

### Output

One item per work:

```json
{
  "openalexId": "W2919115771",
  "doi": "10.1038/nature14539",
  "title": "Deep learning",
  "publicationYear": 2015,
  "publicationDate": "2015-05-26",
  "type": "article",
  "language": "en",
  "authors": [{"name": "Yann LeCun", "orcid": "0000-0002-1992-2684", "position": "first",
               "isCorresponding": true, "institutions": ["Meta (United States)", "New York University"], "countries": ["US"]}],
  "authorNames": ["Yann LeCun", "Yoshua Bengio", "Geoffrey E. Hinton"],
  "firstAuthor": "Yann LeCun",
  "venue": "Nature", "publisher": "Nature Portfolio", "issn": "0028-0836",
  "volume": "521", "issue": "7553", "pages": "436-444",
  "isOA": true, "oaStatus": "green", "oaUrl": "https://hal.science/hal-04206682", "pdfUrl": null, "license": null,
  "citedByCount": 84498, "fwci": 3080.03, "referencedWorksCount": 54, "isRetracted": false,
  "primaryTopic": "Neural Networks and Applications", "field": "Computer Science", "subfield": "Artificial Intelligence",
  "topics": ["Neural Networks and Applications", "..."], "keywords": ["deep learning", "backpropagation"],
  "funders": [], "pmid": "26017442",
  "abstract": "Deep learning allows computational models that are composed of multiple processing layers ...",
  "landingUrl": "https://doi.org/10.1038/nature14539",
  "openalexUrl": "https://openalex.org/W2919115771",
  "source": "OpenAlex (CC0)",
  "searchQuery": "deep learning"
}
```

| Field | Meaning |
|---|---|
| `citedByCount`, `fwci` | Citations received; field-weighted citation impact (1.0 = world average for the field and year). |
| `isOA`, `oaStatus`, `oaUrl`, `pdfUrl`, `license` | Open-access status and the best free-to-read link OpenAlex knows. |
| `primaryTopic`, `field`, `subfield`, `topics` | OpenAlex topic classification (top 3 topics). |
| `abstract` | Rebuilt from OpenAlex's abstract index; `null` when the publisher does not provide one. |

### Pricing

Pay per result: **$0.80 per 1,000 works** (`work-scraped` event). Filters and caps are applied before you are charged, so you pay only for works you receive. A run that finds nothing fails with a clear message instead of returning an empty dataset.

### Limits and notes

- OpenAlex meters API use. Keyless callers share a small daily budget (about 20,000 search results a day per IP). For large or frequent runs, paste your own **free** OpenAlex API key (openalex.org/settings/api) into `apiKey`; it raises the budget 10x and is never logged. If the budget runs out mid-run, the works already returned are kept, the run says it stopped early, and the `SUMMARY` record lists every search with how many works matched and how many were returned.
- Search matches titles and abstracts by default; switch `searchIn` to full text for wider recall. Very broad queries match millions of works; use `maxItems` and filters (each search reaches its first 10,000 results).
- An author name resolves to the main OpenAlex profile with exactly that name (most works), not just the first search hit, and the match is shown in the log and `SUMMARY`. Common names can belong to several people: for an exact person, use their ORCID.
- Some DOIs are listed under a related DOI (for example an arXiv preprint and its published version); unknown DOIs are skipped.
- Abstracts are missing for some publishers that do not share them.

### Data source and credit

Data from [OpenAlex](https://openalex.org) (OurResearch), released under the **CC0** public-domain dedication. Attribution is not required, but credit is appreciated: Priem, J., Piwowar, H., & Orr, R. (2022). *OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts.* arXiv:2205.01833.

This actor is not affiliated with, endorsed by, or sponsored by OpenAlex or OurResearch.

# Actor input Schema

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

Keywords to search in 250M+ scholarly works, one search per line, e.g. `large language models` or `CRISPR off-target`. Each search returns up to Max works per search; a work found by two searches is returned once. Supports AND, OR, NOT and "exact phrases". Leave empty to list works by author, institution or filters alone.

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

One search, the same as one line of Search queries (kept for existing API callers). Supports AND, OR, NOT and "exact phrases".

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

Where the query must match. Title and abstract gives the most relevant results; full text also matches words deep inside papers (more results, less precise).

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

One DOI per line (`10.1038/nature14539` or `https://doi.org/...`). When set, the actor returns exactly these works and ignores the search fields below.

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

Only works by this author (applies to every search). A name (the main OpenAlex profile with that exact name is used, see the log), an ORCID (`0000-0002-1992-2684`) or an OpenAlex author id (`A5108093963`).

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

Only works (in every search) with an author from this institution (including its sub-units). A name (`MIT`, `University of Oxford`), a ROR id or an OpenAlex institution id (`I63966007`).

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

Only works published in or after this year.

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

Only works published in or before this year.

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

Limit to one kind of work.

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

Only works that are free to read somewhere (an OA link is included in each result).

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

Only works cited at least this many times.

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

Two-letter language code, e.g. `en`, `de`, `zh`. Empty = all languages.

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

Relevance to the query, most cited first, or newest first. Without a query, relevance falls back to most cited.

## `includeAbstract` (type: `boolean`):

Adds the abstract (rebuilt from OpenAlex's word index) when the publisher allows it. Turn off for smaller rows.

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

Skip works flagged as retracted.

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

Cap on results for each search (the DOI list returns every DOI found). Also caps your cost; set a maximum charge per run for a hard total.

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

Optional. OpenAlex gives keyless callers a small shared daily budget. For large or frequent runs, paste your own free key from openalex.org/settings/api (10x the daily budget). Never shared or logged.

## Actor input object example

```json
{
  "queries": [
    "large language models"
  ],
  "searchIn": "titleAbstract",
  "type": "any",
  "openAccessOnly": false,
  "sortBy": "relevance",
  "includeAbstract": true,
  "excludeRetracted": true,
  "maxItems": 50
}
```

# Actor output Schema

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

Scholarly works from OpenAlex, one item per work.

# 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": [
        "large language models"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("tidyharvest/openalex-papers-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 = { "queries": ["large language models"] }

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,tidyharvest/openalex-papers-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/EQhcoR405uMxUhjUt/builds/brnnVOPPeQYezohhV/openapi.json