# Wikipedia Article Extractor (`blazing_stake/wikipedia-extractor`) Actor

Fetch clean summaries, descriptions, thumbnails & canonical URLs for Wikipedia articles by title, in any language edition. Official REST API, no key. For knowledge panels & enrichment.

- **URL**: https://apify.com/blazing\_stake/wikipedia-extractor.md
- **Developed by:** [Mehmet Kut](https://apify.com/blazing_stake) (community)
- **Categories:** Developer tools, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$3.00 / 1,000 article extracteds

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/platform/actors/running/actors-in-store#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 Extractor

Fetch clean, structured summaries for Wikipedia articles in **any language edition** via the official Wikipedia REST API. No API key.

### What you get per article

- Title & display title
- Short description
- Plain-text extract (summary)
- Thumbnail & original image URLs
- Canonical page URL, page ID
- Coordinates (for places)

### Input

```json
{
  "titles": ["Apify", "Web scraping", "Istanbul"],
  "language": "en"
}
```

Set `language` to any Wikipedia code — `en`, `tr`, `de`, `fr`, `es`, …

### Output (one record per title)

```json
{
  "query": "Istanbul",
  "found": true,
  "title": "Istanbul",
  "description": "Largest city in Turkey",
  "extract": "Istanbul is the largest city in Turkey...",
  "thumbnail": "https://upload.wikimedia.org/...",
  "url": "https://en.wikipedia.org/wiki/Istanbul"
}
```

### Use cases

- Knowledge panels & tooltips
- Content enrichment for entities/brands/places
- Chatbot & RAG grounding
- Research datasets

Data source: Wikipedia REST API. Pay per article extracted.

# Actor input Schema

## `titles` (type: `array`):

Wikipedia article titles to extract.

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

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

## Actor input object example

```json
{
  "titles": [
    "Istanbul"
  ],
  "language": "en"
}
```

# Actor output Schema

## `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 = {
    "titles": [
        "Apify",
        "Web scraping"
    ]
};

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

# Run the Actor and wait for it to finish
run = client.actor("blazing_stake/wikipedia-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "titles": [
    "Apify",
    "Web scraping"
  ]
}' |
apify call blazing_stake/wikipedia-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=blazing_stake/wikipedia-extractor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/NFGzwe9oyTt5VK5mw/builds/bnxaKyImIAJklq969/openapi.json