# Wikipedia Article Scraper: Search, Summaries & Text (`cynix_dev/wikipedia-article-scraper`) Actor

Search Wikipedia, fetch article summaries (extracts) or random articles across languages. Keyless, for RAG and reference data.

- **URL**: https://apify.com/cynix\_dev/wikipedia-article-scraper.md
- **Developed by:** [Cynix Dev](https://apify.com/cynix_dev) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.25 / 1,000 results

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?

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

## Wikipedia Article Scraper: Search, Summaries & Text

Search **Wikipedia**, fetch article summaries (extracts) or random articles across languages — keyless, for RAG and reference data.

![Wikipedia](https://img.logo.dev/wikipedia.org?token=pk_f3e1270e3c2e4cb5a0c3a8d86e96b90a\&size=200\&retina=true\&format=png)

### What it does

Clean, structured access to the world's largest encyclopedia (60M+ articles, 300+ languages) via the official MediaWiki REST + Action APIs.

### Modes

| Mode | What it returns |
|------|-----------------|
| **search** | Search results with article summaries |
| **article** | Full summary/extract of one article by title |
| **random** | Pull random articles (useful for sampling) |

### Example Inputs

#### Search for AI

```json
{ "mode": "search", "query": "artificial intelligence", "searchLimit": 10, "language": "en" }
```

#### Get one article

```json
{ "mode": "article", "query": "Transformer (machine learning)", "language": "en" }
```

#### Spanish-language random articles

```json
{ "mode": "random", "searchLimit": 5, "language": "es" }
```

### Output

Per article: `title`, `display_title`, `description`, `thumbnail_url`, `extract`, `url`, `categories`, `language`, `search_query`, `scraped_at`.

### Use Cases

- **RAG knowledge bases**: extract-rich article summaries for AI pipelines
- **Content research**: facts and background across any topic
- **Multilingual data**: pull article summaries in 300+ languages
- **Education / reference**: structured encyclopedia content

### Data Source

[Wikipedia / MediaWiki](https://www.mediawiki.org/wiki/API) — free, keyless, CC BY-SA content.

### Limitations

- Summaries are the intro/extract (not full article text)
- Respects rate limits (the actor paces requests)

# Actor input Schema

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

Which Wikipedia data to fetch.

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

Search term (search mode) or exact article title (article mode).

## `searchLimit` (type: `integer`):

Max search results or random articles.

## `withExtract` (type: `boolean`):

Include the plain-text article summary.

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

Language code (en, es, de, fr, etc.).

## Actor input object example

```json
{
  "mode": "search",
  "query": "artificial intelligence",
  "searchLimit": 10,
  "withExtract": true,
  "language": "en"
}
```

# Actor output Schema

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

Dataset containing all scraped records

# 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 = {
    "query": "artificial intelligence",
    "language": "en"
};

// Run the Actor and wait for it to finish
const run = await client.actor("cynix_dev/wikipedia-article-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 = {
    "query": "artificial intelligence",
    "language": "en",
}

# Run the Actor and wait for it to finish
run = client.actor("cynix_dev/wikipedia-article-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 '{
  "query": "artificial intelligence",
  "language": "en"
}' |
apify call cynix_dev/wikipedia-article-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,cynix_dev/wikipedia-article-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/5y0FGOo7hBOurUkLQ/builds/Rf99UycKfdd6cXQlk/openapi.json