# Article Extractor: News & Blog Text, RSS, $2/1K, No Login (`conserving_celerytop/article-extractor`) Actor

Extract clean article text from news and blog pages: title, publication date, site, language, description, image, word count and reading time, as text, Markdown or HTML. Paste article URLs or RSS, Atom and sitemap feeds. $2 per 1,000 articles; pages with no article are free.

- **URL**: https://apify.com/conserving\_celerytop/article-extractor.md
- **Developed by:** [Don Mangu](https://apify.com/conserving_celerytop) (community)
- **Categories:** News, AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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/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

For AI agents: pass article URLs, or RSS, Atom or sitemap feeds; get one JSON row per article with clean text (or Markdown or HTML), title, publication date, site name, language, main image, word count and reading time. Pages that are not articles, and articles older than your date filter, return free rows.

Cost: $0.002 per article extracted ($2 per 1,000). Pages with no article, blocked or missing pages, and feed errors are free. No login or API key.

### What does Article Extractor do?

It reads news stories, blog posts, press releases and guides and returns the article itself: the text without menus, ads, related-story lists and comment sections, plus the details a reader or a pipeline needs. You can give it article addresses, or give it RSS, Atom or XML sitemap feeds and it picks the newest articles from each.

- **Media monitoring:** follow the feeds of news sites, agencies and blogs and get each new article's text once, on a schedule.
- **RAG and research:** build a clean corpus of articles on a topic, with dates and sources.
- **Content teams:** read the length, date and summary of many articles at once.
- **AI agents:** give an agent the readable text of an article through the Apify API or Apify's MCP server.

**Try it now.** The form opens with a NASA science story and NASA's news feed (3 newest articles). Click **Start**; it takes a few seconds and costs under a cent.

### How to extract articles from URLs or RSS feeds

1. Paste article addresses into **Article URLs**, or feed and sitemap addresses into **Feeds and sitemaps**, or both.
2. Set **Articles per feed** (the newest ones are taken) and, if you want, **Published since** (a date or a period such as 7 days).
3. Pick the **Output formats**: plain text, Markdown, clean HTML, or several.
4. For monitoring, turn on **Only new articles since my last run**, give it a **Monitor name**, and schedule the Actor. Each run returns only articles it has not returned before.
5. Click **Start**, then open the **Articles** or **Article text** table, or download JSON, CSV or Excel.

### How much does article extraction cost?

**$0.002 per article extracted** ($2 per 1,000 articles). Free rows: pages with no article (home pages, lists, forms), articles older than your date filter, pages that are blocked, missing or not allowed by robots.txt, and feeds that cannot be read. Apify adds only its small standard fee per run start.

Example: you follow 30 news feeds every morning with **Only new articles** on. About 400 new articles appear each day, so a day costs 400 x $0.002 = **$0.80**, about $24 a month. You can set a spending limit on any run, and the Actor stops cleanly when it is reached.

### Input

```json
{
  "articleUrls": ["https://www.nasa.gov/centers-and-facilities/goddard/decoding-extreme-weather-at-the-poles/"],
  "feedUrls": ["https://www.nasa.gov/news-release/feed/"],
  "maxArticlesPerFeed": 3,
  "publishedSince": "7 days",
  "outputFormats": ["text"],
  "onlyNewArticles": false
}
```

Advanced options: maximum articles per run (up to 5,000), images kept in the Markdown and HTML, maximum characters per article, articles at a time (at most 2 at a time go to the same site) and a timeout per page.

### Output

```json
{
  "url": "https://science.nasa.gov/earth/earth-observatory/uncovering-the-valleys-hidden-below-greenlands-ice/",
  "status": "ok",
  "source": "feed",
  "feedUrl": "https://www.nasa.gov/news-release/feed/",
  "title": "Uncovering the Valleys Hidden Below Greenland’s Ice - NASA Science",
  "siteName": "NASA Science",
  "language": "en-US",
  "publishedAt": "2026-09-28T04:00:00.000Z",
  "imageUrl": "https://assets.science.nasa.gov/...",
  "excerpt": "Greenland is capped with a vast ice sheet that spans 1.7 million square kilometers ...",
  "text": "Greenland is capped with a vast ice sheet ...",
  "wordCount": 688,
  "readingTimeMinutes": 3,
  "truncated": false,
  "charged": true,
  "error": null
}
```

`status` is `ok` for extracted articles, which are charged. The free statuses are `not_article`, `too_old`, `blocked`, `robots_disallowed`, `robots_unreachable`, `http_error`, `not_found`, `timeout`, `not_html`, `invalid_url`, `feed_error` and `not_a_feed`, each with an `error` that says why. A STATS record in the key-value store counts articles by status, charges, feed items and time.

### How does it tell an article from other pages?

A page counts as an article when its main content is long enough to be an article and, for a page given by address, the page marks itself as one (a schema.org Article, NewsArticle or BlogPosting) or states a publication date. Pages from a feed or sitemap are treated as articles when their main content is found. Home pages, section pages and lists come back as free `not_article` rows with their title.

### Related

- [Web Page to Markdown](https://apify.com/conserving_celerytop/web-page-to-markdown): any page, not only articles, as Markdown for LLMs, with JavaScript rendering when a page needs it.

### FAQ

**Does it respect robots.txt?** Yes. It reads each site's robots.txt and skips pages and feeds the site does not allow for the token `DonMangu-ArticleExtractor` or for all crawlers. Those rows are free.

**Can it read paywalled articles?** No. It reads public pages only and does not log in. A paywall or login page comes back as `blocked` (free), and a page that shows only a teaser gives the teaser.

**Does it return author names?** No. It returns the article and page-level details, not personal details about authors.

**Can I reuse the articles?** The text belongs to its publishers. Check each site's terms before you republish anything; the Actor is meant for reading, research, monitoring and analysis.

**How are sitemaps handled?** For a sitemap index, it reads the article sitemaps (news, press, blog and post sitemaps) and skips people, category, page and media sitemaps, then takes the newest entries by date.

# Actor input Schema

## `articleUrls` (type: `array`):

Enter the addresses of article pages, one per line: news stories, blog posts, press releases or guides.

## `feedUrls` (type: `array`):

Enter RSS, Atom or XML sitemap addresses, one per line. The newest articles of each are read, up to Articles per feed.

## `maxArticlesPerFeed` (type: `integer`):

Read at most this many of the newest articles from each feed or sitemap.

## `publishedSince` (type: `string`):

Keep only articles published on or after this date, as 2026-09-01 or a period such as 24 hours or 7 days. Older feed and sitemap items are skipped before they are read; an article URL published earlier gives a free row marked too\_old. Leave empty for all dates.

## `outputFormats` (type: `array`):

Pick the formats to return for each article.

## `maxArticles` (type: `integer`):

Read at most this many articles in the run, from URLs and feeds together, up to 5,000.

## `onlyNewArticles` (type: `boolean`):

Skip articles returned by an earlier run with the same Monitor name. Schedule the Actor to get each new article once.

## `monitorName` (type: `string`):

A name for this list of feeds, so several monitors can run side by side. Letters, digits and dashes.

## `includeImages` (type: `boolean`):

Keep images inside the article in the Markdown and HTML output. The main image of each article is in imageUrl either way.

## `maxCharacters` (type: `integer`):

Cut the text, Markdown and HTML at this many characters. The row then has truncated set to true.

## `maxConcurrency` (type: `integer`):

How many articles to read in parallel, 1 to 20. At most 2 at a time go to the same site.

## `timeoutSecs` (type: `integer`):

How long to wait for one page or feed, 5 to 120 seconds.

## Actor input object example

```json
{
  "articleUrls": [
    "https://www.nasa.gov/centers-and-facilities/goddard/decoding-extreme-weather-at-the-poles/"
  ],
  "feedUrls": [
    "https://www.nasa.gov/news-release/feed/"
  ],
  "maxArticlesPerFeed": 3,
  "outputFormats": [
    "text"
  ],
  "maxArticles": 100,
  "onlyNewArticles": false,
  "monitorName": "default",
  "includeImages": false,
  "maxCharacters": 100000,
  "maxConcurrency": 5,
  "timeoutSecs": 30
}
```

# Actor output Schema

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

Date, title, site and length per article.

## `text` (type: `string`):

Title, excerpt and text per article.

## `all` (type: `string`):

Every row with every field.

## `stats` (type: `string`):

Articles read, charges, feeds and time.

# 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 = {
    "articleUrls": [
        "https://www.nasa.gov/centers-and-facilities/goddard/decoding-extreme-weather-at-the-poles/"
    ],
    "feedUrls": [
        "https://www.nasa.gov/news-release/feed/"
    ],
    "maxArticlesPerFeed": 3,
    "outputFormats": [
        "text"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("conserving_celerytop/article-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 = {
    "articleUrls": ["https://www.nasa.gov/centers-and-facilities/goddard/decoding-extreme-weather-at-the-poles/"],
    "feedUrls": ["https://www.nasa.gov/news-release/feed/"],
    "maxArticlesPerFeed": 3,
    "outputFormats": ["text"],
}

# Run the Actor and wait for it to finish
run = client.actor("conserving_celerytop/article-extractor").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 '{
  "articleUrls": [
    "https://www.nasa.gov/centers-and-facilities/goddard/decoding-extreme-weather-at-the-poles/"
  ],
  "feedUrls": [
    "https://www.nasa.gov/news-release/feed/"
  ],
  "maxArticlesPerFeed": 3,
  "outputFormats": [
    "text"
  ]
}' |
apify call conserving_celerytop/article-extractor --silent --output-dataset

```

## MCP server setup

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

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/sJNhurLYtUR1lQcAy/builds/1srpDf9I7haNEetGh/openapi.json