# Wikipedia Change Intelligence (`glowing_glove/wikipedia-change-intelligence`) Actor

Watch Wikipedia entities and return summaries, revision timestamps, changed sections, links, and knowledge-base update signals.

- **URL**: https://apify.com/glowing\_glove/wikipedia-change-intelligence.md
- **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community)
- **Categories:** News, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 wikipedia entity rows

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?

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 Change Intelligence

Watch Wikipedia entities and return summaries, revision timestamps, changed sections, links, and knowledge-base update signals.

Wikipedia Change Intelligence is built for buyers who need clean, source-backed data they can export into spreadsheets, CRMs, dashboards, alerts, or enrichment workflows. The actor focuses on the business object promised by its name and avoids dumping raw HTML, debug metadata, run timestamps, actor names, or unrelated crawl noise into successful dataset rows.

### Who Uses It

- research teams
- brand monitors
- knowledge-base editors
- PR analysts

### What It Extracts

- Entity
- Page Title
- Revision Date
- Editor
- Change Summary
- Diff Url
- Watch Reason
- Signal Score

### Input

Use the input fields in the Apify UI to provide the public URLs, keywords, companies, pages, profiles, tickers, topics, or source lists relevant to this actor. Keep the first run small, inspect the dataset, and then raise limits or schedule recurring runs when the rows match your workflow.

### Output You Get

Successful dataset rows are compact and actor-specific. Important fields include:

- `entity`
- `pageTitle`
- `revisionDate`
- `editor`
- `changeSummary`
- `diffUrl`
- `watchReason`
- `signalScore`

Failure rows, when needed, include a short error or warning so you can fix bad inputs or blocked sources. Successful rows do not include unnecessary run metadata such as actor name, started time, finished time, raw input echo, or generic status noise.

### Good Use Cases

- Build focused lead lists or research tables from public sources.
- Monitor changes and signals that matter for sales, SEO, ecommerce, marketing, product, or research workflows.
- Export clean rows to Google Sheets, Airtable, BI tools, CRM systems, or automation pipelines.
- Run small tests before scaling to larger scheduled jobs.

### Reliability Notes

The actor uses guarded limits, request timeouts, retries where useful, and compact output rows. Public websites can change, block traffic, or hide data behind login walls; when that happens, the actor returns useful warnings instead of charging for empty success rows whenever the implementation can avoid it.

# Actor input Schema

## `entities` (type: `array`):

Wikipedia page names such as OpenAI, Nvidia, Dubai, or Tesla, Inc.

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

Maximum dataset rows to write. Keep low for tests to control cloud cost.

## `monitorChanges` (type: `boolean`):

Save a snapshot and compare future runs.

## `onlyChanges` (type: `boolean`):

When monitoring is enabled, output only new or changed rows.

## `maxRunSeconds` (type: `integer`):

Hard runtime guard to avoid timeout and spend surprises.

## `requestTimeoutSeconds` (type: `integer`):

Timeout per public HTTP request.

## Actor input object example

```json
{
  "entities": [
    "OpenAI",
    "Nvidia"
  ],
  "maxResults": 10,
  "monitorChanges": false,
  "onlyChanges": false,
  "maxRunSeconds": 180,
  "requestTimeoutSeconds": 15
}
```

# Actor output Schema

## `results` (type: `string`):

Open the clean dataset rows produced by Wikipedia Change Intelligence.

# 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 = {
    "entities": [
        "OpenAI",
        "Nvidia"
    ],
    "maxResults": 10,
    "monitorChanges": false,
    "onlyChanges": false,
    "maxRunSeconds": 180,
    "requestTimeoutSeconds": 15
};

// Run the Actor and wait for it to finish
const run = await client.actor("glowing_glove/wikipedia-change-intelligence").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 = {
    "entities": [
        "OpenAI",
        "Nvidia",
    ],
    "maxResults": 10,
    "monitorChanges": False,
    "onlyChanges": False,
    "maxRunSeconds": 180,
    "requestTimeoutSeconds": 15,
}

# Run the Actor and wait for it to finish
run = client.actor("glowing_glove/wikipedia-change-intelligence").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 '{
  "entities": [
    "OpenAI",
    "Nvidia"
  ],
  "maxResults": 10,
  "monitorChanges": false,
  "onlyChanges": false,
  "maxRunSeconds": 180,
  "requestTimeoutSeconds": 15
}' |
apify call glowing_glove/wikipedia-change-intelligence --silent --output-dataset

```

## MCP server setup

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

```

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/w0shKRCg28oXC7Ico/builds/EPQ1Eoi20DMROLfFW/openapi.json