# Scholarly Papers Search (Google Scholar alternative, OpenAlex) (`mediapro-tools/openalex-scholar-papers`) Actor

Search 250M+ scholarly works via the official OpenAlex API: DOI, authors, citations, open-access PDF links, abstracts. No login. Export JSON/CSV/Excel. Pay only per result.

- **URL**: https://apify.com/mediapro-tools/openalex-scholar-papers.md
- **Developed by:** [Jeremy Yarbrough](https://apify.com/mediapro-tools) (community)
- **Categories:** AI, Lead generation, 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 paper records

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

## Scholarly Papers Search (Google Scholar alternative, OpenAlex)

**Search 250M+ scholarly works via the official OpenAlex API: DOI, authors, citations, open-access PDF links, abstracts, with no login, no browser and no code. Export to JSON, CSV or Excel, or use the API.**

Search 250M+ scholarly works through the official OpenAlex API: title, DOI, authors, institutions, venue, year, citation count, open-access PDF link, topics and abstract. Search by keyword, author name or DOI list, filter by year/open access/type, sort by citations or newest, and monitor new papers per query.

### Use cases

- Literature reviews and citation-ranked reading lists
- Find researchers / institutions for B2B outreach in a field
- Alerts on new papers for a topic or author

### Input

| Field | Type | Notes |
|---|---|---|
| `queries` | array | Keywords searched in title, abstract and full text. |
| `authorNames` | array | Return works by the best-matching OpenAlex author. |
| `dois` | array | Look up specific papers by DOI or doi.org URL. |
| `fromYear` | integer |  |
| `toYear` | integer |  |
| `openAccessOnly` | boolean |  |
| `workType` | string |  |
| `sortBy` | string |  |
| `maxResultsPerQuery` | integer |  |
| `includeAbstract` | boolean |  |
| `contactEmail` | string | Sent to OpenAlex for its faster polite pool. |
| `monitorMode` | boolean | Remember seen works per query; later runs flag/output only new ones. |
| `stateStoreName` | string |  |

### Example input

```json
{
 "queries": [
  "large language models agriculture"
 ],
 "authorNames": [
  "Geoffrey Hinton"
 ],
 "dois": [
  "10.1038/nature14539",
  "10.9999/not-a-real-doi-zz"
 ],
 "maxResultsPerQuery": 3,
 "sortBy": "citations",
 "monitorMode": true
}
```

### Output

One dataset item per result. Main columns: `title`, `publicationYear`, `venue`, `authors`, `citedByCount`, `isOpenAccess`, `pdfUrl`, `doi`, `isNew`, `error`. A `RUN_SUMMARY` record is saved to the default key-value store. See the sample output in the Output tab.

### OpenAlex API key (optional)

OpenAlex's API has a small free daily budget without a key. For large jobs, paste your own free key from openalex.org/settings/api into `apiKey`; OpenAlex usage then counts against your key (10x budget, pay-as-you-go beyond). The run summary reports `apiCostUsd`.

### Example output

```json
{
  "input": "10.1038/nature14539",
  "openalexId": "https://openalex.org/W2919115771",
  "doi": "https://doi.org/10.1038/nature14539",
  "title": "Deep learning",
  "publicationYear": 2015,
  "publicationDate": "2015-05-26",
  "type": "article",
  "venue": "Nature",
  "publisher": "Nature Portfolio",
  "authors": [
    "Yann LeCun",
    "Yoshua Bengio",
    "Geoffrey E. Hinton"
  ],
  "institutions": [
    "Meta (United States)",
    "New York University",
    "Université de Montréal"
  ],
  "citedByCount": 84498,
  "fwci": 3080.0301,
  "isOpenAccess": true,
  "oaStatus": "green",
  "pdfUrl": "https://hal.science/hal-04206682",
  "landingPageUrl": "https://doi.org/10.1038/nature14539",
  "topics": [
    "Neural Networks and Applications",
    "Advanced Neural Network Applications",
    "Domain Adaptation and Few-Shot Learning"
  ]
}
```

### Pricing

Pay per result, with no monthly rental or subscription:

- **Paper record**: $0.001

Example: 1,000 results cost about $1.00 in fees. Apify's free plan includes $5 of monthly credit, which is enough to test this Actor.

### FAQ

**Do I need an account, cookies or a login for the source site?** No. Scholarly Papers Search uses public data sources only, so there is nothing to connect and no account to risk.

**How much will a run cost?** You pay only for results delivered (see Pricing above), plus Apify platform usage, which the free plan's monthly credit easily covers for test runs. Start with a small limit to see the exact cost per run.

**Can I export to CSV, Excel or Google Sheets?** Yes. Every run's dataset can be downloaded as JSON, CSV, Excel, XML or HTML, or pushed to Google Sheets, Make, Zapier, n8n, Slack or a webhook through Apify integrations.

**Can I run it on a schedule or from my own code?** Yes. Add an Apify Schedule (hourly, daily, weekly) or call it through the Apify API / Python & JavaScript clients. It also works with AI agents through the Apify MCP server.

**What happens if an input is invalid or a source is down?** The run keeps going. The bad input gets a row with an `error` field so you can see what failed, and you are not charged for results that were not delivered.

**Is this legal to use?** It collects publicly available data. You are responsible for using the output in line with the source's terms and privacy laws such as GDPR/CCPA; don't use it for spam.

**Something missing or broken?** Open an issue on the Issues tab. Feature requests are usually added within a few days.

### Scheduling / monitoring

Create a Schedule (daily/weekly) and connect a webhook or Slack/email integration.

### Fair use

Official public APIs only, no login. Do not use output for spam or harassment. Respect the data sources' rate limits and terms.

### Related tools

- [Hugging Face Models, Datasets & Spaces Scraper + Trend Tracker](https://apify.com/mediapro-tools/hugging-face-models-datasets-tracker)
- [SEC EDGAR Filings Scraper & Monitor: 10-K, 10-Q, 8-K, Form 4](https://apify.com/mediapro-tools/sec-edgar-filings-monitor)
- [Bulk ISBN Lookup: Book Title, Author, Covers & Metadata](https://apify.com/mediapro-tools/isbn-book-metadata-lookup)
- [GitHub Repo Stats & Release Tracker (official API)](https://apify.com/mediapro-tools/github-repo-release-tracker)

### REST API

`GET https://api.mediaprotools.com/v1/openalex-scholar?items=...` (header `X-API-Key`). Up to 5 items per call, separated by `,`. Or POST `{"items":[...],"options":{...}}`.

| Parameter | Type | Notes |
|---|---|---|
| `items` | token | Keywords searched in title, abstract and full text. |
| `authorNames` | array | Return works by the best-matching OpenAlex author. |
| `dois` | array | Look up specific papers by DOI or doi.org URL. |
| `fromYear` | integer 1800-2100 | From year |
| `toYear` | integer 1800-2100 | To year |
| `openAccessOnly` | boolean | Open access only |
| `workType` | string | Work type |
| `sortBy` | string | Sort by |
| `maxResultsPerQuery` | integer 1-100 | Max results per query/author |
| `includeAbstract` | boolean | Include abstract |
| `contactEmail` | string | Sent to OpenAlex for its faster polite pool. |
| `apiKey` | string | Free key from openalex.org/settings/api. Without it, runs share OpenAlex's small keyless daily budget and large jobs may stop with a budget error. With it, OpenAlex usage counts against your own free (10x) or paid budget. |

Output fields: abstract, authors, citedByCount, doi, fwci, input, institutions, isNew, isOpenAccess, keywords, landingPageUrl, language, oaStatus, openalexId, pdfUrl, publicationDate, publicationYear, publisher, referencedWorksCount, retracted, title, topics, totalMatches, type, venue.

# Actor input Schema

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

Keywords searched in title, abstract and full text.

## `authorNames` (type: `array`):

Return works by the best-matching OpenAlex author.

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

Look up specific papers by DOI or doi.org URL.

## `fromYear` (type: `integer`):

No description

## `toYear` (type: `integer`):

No description

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

No description

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

No description

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

No description

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

No description

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

No description

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

Sent to OpenAlex for its faster polite pool.

## `monitorMode` (type: `boolean`):

Remember seen works per query; later runs flag/output only new ones.

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

No description

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

Free key from openalex.org/settings/api. Without it, runs share OpenAlex's small keyless daily budget and large jobs may stop with a budget error. With it, OpenAlex usage counts against your own free (10x) or paid budget.

## Actor input object example

```json
{
  "queries": [
    "large language models agriculture"
  ],
  "openAccessOnly": false,
  "workType": "",
  "sortBy": "relevance",
  "maxResultsPerQuery": 100,
  "includeAbstract": true,
  "monitorMode": false,
  "stateStoreName": "openalex-monitor"
}
```

# Actor output Schema

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

All result records in the default dataset (table view: overview).

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

Files saved by this run (download links are also in each result record).

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

Counts and stats for this run (JSON).

# 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 agriculture"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("mediapro-tools/openalex-scholar-papers").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 agriculture"] }

# Run the Actor and wait for it to finish
run = client.actor("mediapro-tools/openalex-scholar-papers").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 agriculture"
  ]
}' |
apify call mediapro-tools/openalex-scholar-papers --silent --output-dataset

```

## MCP server setup

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

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/yiswJenwix6GAFhRi/builds/GWZLw1rB2DPoTRYzg/openapi.json