# Wikipedia Search & Article Extract - MediaWiki API (`channel_l/wikipedia-search-extract`) Actor

Search Wikipedia & get article intros across any language (MediaWiki API, no key). Topics in, title, page ID, snippet, extract out. Knowledge bases, NLP, research.

- **URL**: https://apify.com/channel\_l/wikipedia-search-extract.md
- **Developed by:** [Channel L](https://apify.com/channel_l) (community)
- **Categories:** Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 article 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?

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 Search & Article Extract

Search **Wikipedia** and optionally fetch the article's intro/abstract, across any language, via the free public MediaWiki API. No API key required.

### Input

| Field | Type | Description |
|---|---|---|
| queries | string (req) | Comma-separated topics to search |
| language | string | Wikipedia lang code (en, id, es...) |
| limit | integer | Max articles per query |
| includeExtract | boolean | Fetch first paragraph of each article |

### Output (per article)

`{ query, lang, title, pageid, snippet, extract }`

### Why

- Knowledge base building, NLP datasets, encyclopedic reference, research, content augmentation
- Free, public, no key, multi-language

# Actor input Schema

## `queries` (type: `string`):

Comma-separated topics to search Wikipedia.

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

Wikipedia language code (en, id, es, etc).

## `limit` (type: `integer`):

Max articles per query.

## `includeExtract` (type: `boolean`):

Fetch first paragraph of each article.

## Actor input object example

```json
{
  "queries": "Bitcoin, Artificial intelligence",
  "language": "en",
  "limit": 3,
  "includeExtract": true
}
```

# Actor output Schema

## `datasetJson` (type: `string`):

Link to full dataset in JSON.

## `datasetCsv` (type: `string`):

Download articles as CSV.

## `totalArticles` (type: `string`):

Number of article records in dataset.

# 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": "Bitcoin, Artificial intelligence",
    "language": "en"
};

// Run the Actor and wait for it to finish
const run = await client.actor("channel_l/wikipedia-search-extract").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": "Bitcoin, Artificial intelligence",
    "language": "en",
}

# Run the Actor and wait for it to finish
run = client.actor("channel_l/wikipedia-search-extract").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": "Bitcoin, Artificial intelligence",
  "language": "en"
}' |
apify call channel_l/wikipedia-search-extract --silent --output-dataset

```

## MCP server setup

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

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/KO5oyTEabOZGHeDpB/builds/8BV2WcdHpqwycT704/openapi.json