# CORE Open Research Scraper (`searchapi/core-open-research-scraper`) Actor

Search CORE's public open-access research index with bounded pagination, stable normalization, deduplication, safe retries, and optional proxies.

- **URL**: https://apify.com/searchapi/core-open-research-scraper.md
- **Developed by:** [Search API](https://apify.com/searchapi) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.99 / 1,000 search results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## CORE Open Research Scraper

Search CORE's public open-access works index using a topic, title, author, DOI, institution, or CORE query expression. The Actor follows the public API's offset pagination and returns a compact, stable dataset of real works.

### Input example

```json
{
  "query": "machine learning",
  "maxItems": 50,
  "pageSize": 25,
  "maxPages": 2,
  "requestDelayMs": 300,
  "useApifyProxy": false
}
```

`maxResults` remains a backward-compatible alias for `maxItems`. The Actor supports direct access, authorized Apify Proxy groups/country selection, or custom HTTP(S) proxy URLs.

### Output

Each dataset row contains a stable CORE identity, title, deduplicated author names, public CORE URL, query/page/rank context, and optional abstract, DOI, type, publisher, field, dates, citations, and public download URL. Missing optional values are omitted. Failures and no-results never become placeholder work rows; the `OUTPUT` key contains status, page counts, total hits, bounded failure categories, connection mode, and completion time.

The Actor validates HTTP status and content type before parsing JSON, enforces a response-size bound, rejects malformed or changed payloads, retries only temporary failures, deduplicates by CORE ID, and obeys hard page/result limits. It never stores raw API payloads or logs proxy credentials, authorization headers, cookies, tokens, or sensitive response bodies. It does not bypass authentication, CAPTCHA, paywalls, regional restrictions, or other access controls.

# Changelog

This Actor's version history is a separate document: https://apify.com/searchapi/core-open-research-scraper/changelog.md

# Actor input Schema

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

Topic, title, author, DOI, institution, or CORE query expression.

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

Hard global result limit.

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

Backward-compatible alias for maxItems.

## `pageSize` (type: `integer`):

Works requested per CORE API page.

## `maxPages` (type: `integer`):

Hard API pagination limit.

## `requestDelayMs` (type: `integer`):

Polite delay between pages in milliseconds.

## `requestTimeoutSecs` (type: `integer`):

Maximum seconds for one CORE request.

## `maxRequestRetries` (type: `integer`):

Retries for temporary network, rate-limit, and server failures.

## `useApifyProxy` (type: `boolean`):

Route requests through an authorized Apify Proxy configuration.

## `proxyGroups` (type: `array`):

Optional authorized Apify Proxy groups.

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

Optional two-letter country code.

## `proxyUrls` (type: `array`):

Optional HTTP(S) proxy URLs; credentials are never logged or stored.

## Actor input object example

```json
{
  "query": "machine learning",
  "maxItems": 50,
  "pageSize": 50,
  "maxPages": 1,
  "requestDelayMs": 300,
  "requestTimeoutSecs": 60,
  "maxRequestRetries": 2,
  "useApifyProxy": false,
  "proxyGroups": [],
  "proxyUrls": []
}
```

# Actor output Schema

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

No description

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

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/core-open-research-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("searchapi/core-open-research-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 '{}' |
apify call searchapi/core-open-research-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,searchapi/core-open-research-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/xHIiwmIL6LiQ5y5Xx/builds/VFdKcB7tStrAGNEJh/openapi.json