# Wikipedia Article Extractor: Clean Text, Categories & Wikidata (`shawndunn/wikipedia-article-text`) Actor

Get clean plain text (intro or full article) for Wikipedia articles in any language, plus categories, Wikidata ID, short description, image, language count and last edit. Search mode included. Extracts fields: language, title, pageId, url, wikidataId, shortDescription, isDisambiguation, intro.

- **URL**: https://apify.com/shawndunn/wikipedia-article-text.md
- **Developed by:** [CarrierDaily](https://apify.com/shawndunn) (community)
- **Categories:** AI, Other
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.80 / 1,000 articles

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

## Wikipedia Article Extractor: Clean Text, Categories & Wikidata

Get clean plain text (intro or full article) for Wikipedia articles in any language, plus categories, Wikidata ID, short description, image, language count and last edit. Search mode included.

### Why this actor

- LLM-ready clean text with entity IDs to join to Wikidata.
- Pay only for results: **$0.80 per 1,000 articles**, no start fee, failed lookups are free.
- Robust: automatic retries with exponential backoff, respects `Retry-After`, per-item error rows instead of crashed runs.
- Clean, flat JSON/CSV/Excel output ready for Google Sheets, Make, Zapier, n8n, Clay, or the Apify API.

### Use cases

- RAG/LLM knowledge ingestion
- Entity enrichment for company/product databases
- Education and research datasets
- Multilingual content comparison

### Input

| Field | Type | Description |
|---|---|---|
| `articles` | array | Titles or Wikipedia URLs (redirects followed). |
| `search` | string | Full-text search; adds matching articles. |
| `maxSearchResults` | integer | Cap. |
| `language` | string | Wikipedia language code (en, de, fr, es, ja...). |
| `fullText` | boolean | Whole article as clean text (for LLM/RAG). Off = intro only. |
| `maxItems` | integer | 0 = no limit. Caps cost. |

Example input:

```json
{
  "articles": [
    "Web scraping",
    "https://en.wikipedia.org/wiki/Denver"
  ],
  "search": "open data",
  "maxSearchResults": 3
}
```

### Output

Each dataset item looks like this (real sample from a test run, long fields trimmed):

```json
{
  "language": "en",
  "title": "Web scraping",
  "pageId": 2696619,
  "url": "https://en.wikipedia.org/wiki/Web_scraping",
  "wikidataId": "Q665452",
  "shortDescription": "Method of extracting data from websites",
  "isDisambiguation": false,
  "intro": "Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. Web scraping software may directly access the World Wide Web using the Hypertext Transfer Protocol or a web browser. While web scr\u2026",
  "wordCount": 436,
  "categories": [
    "Web scraping"
  ],
  "languagesCount": 22,
  "image": null,
  "pageLengthBytes": 34836,
  "lastEditedAt": "2026-09-19T09:13:04Z",
  "scrapedAt": "2026-10-14T16:21:17+00:00"
}
```

Rows that could not be processed contain an `error` field and are **not charged**.

### Pricing

Pay-per-event: **$0.0008** per article (= $0.80 / 1,000). Use **Max results** to cap spend. Apify's free plan credit covers thousands of results per month.

### Integrations & API

Run on a schedule in Apify Console, call via the Apify API / Python & JS clients, or connect to Make, Zapier, n8n, Google Sheets, Slack and webhooks. Works as a tool for AI agents via Apify MCP.

### FAQ

**Is this an official tool?** No. It is an independent actor and is not affiliated with, sponsored or endorsed by the data source or any trademark owner named here.

**Is it legal?** The actor only reads publicly available data from public endpoints, without logins, and does not bypass paywalls or access controls. You are responsible for using the data in line with applicable laws (e.g. GDPR) and the source sites' terms.

**Something broke?** Open an issue in the Issues tab; we typically respond within 24 hours and ship fixes fast.

# Actor input Schema

## `articles` (type: `array`):

Titles or Wikipedia URLs (redirects followed).

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

Full-text search; adds matching articles.

## `maxSearchResults` (type: `integer`):

Cap.

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

Wikipedia language code (en, de, fr, es, ja...).

## `fullText` (type: `boolean`):

Whole article as clean text (for LLM/RAG). Off = intro only.

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

0 = no limit. Caps cost.

## Actor input object example

```json
{
  "articles": [
    "Apify",
    "Web scraping"
  ],
  "maxSearchResults": 20,
  "language": "en",
  "fullText": false,
  "maxItems": 0
}
```

# Actor output Schema

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

No description

## `results` (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 = {
    "articles": [
        "Apify",
        "Web scraping"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("shawndunn/wikipedia-article-text").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 = { "articles": [
        "Apify",
        "Web scraping",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("shawndunn/wikipedia-article-text").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 '{
  "articles": [
    "Apify",
    "Web scraping"
  ]
}' |
apify call shawndunn/wikipedia-article-text --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,shawndunn/wikipedia-article-text"
        }
    }
}
```

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/DLw1ZoZ9dZhWpIK54/builds/QIFwrjs6h7Pyrom5v/openapi.json