RSS & News Feed Aggregator — Multi-Source Article Scraper

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Aggregate and parse multiple RSS 2.0 and Atom feeds into clean, structured data. Built for monitoring, curation, and intelligence workflows.

Features

• Multi-format support — RSS 2.0, RSS 1.0 (RDF), and Atom feeds
• Namespace handling — Parses media:, dc:, content:encoded, and standard Atom namespaces
• Full content extraction — Optionally follows article links and strips HTML to plain text
• Robust parsing — Handles encoding issues, CDATA blocks, malformed dates, and missing fields
• Structured output — Consistent schema across all feed types

Output Schema

Each article in the dataset contains:

Input Parameters

{
"feedUrls":[
"https://feeds.bbci.co.uk/news/rss.xml",
"https://rss.nytimes.com/services/xml/rss/index.xml",
"https://hnrss.org/frontpage"
],
"maxArticles":100,
"fetchFullContent":false
}

• feedUrls (required) — Array of RSS/Atom feed URLs to aggregate
• maxArticles (default: 100) — Maximum articles to output. Set to 0 for unlimited.
• fetchFullContent (default: false) — Follow article links and extract full text content

Use Cases

📡 News Monitoring & Media Intelligence

Track coverage across dozens of news outlets. Monitor specific topics by aggregating topic-specific RSS feeds from major publishers. Feed results into sentiment analysis or trend detection pipelines.

📋 Content Curation & Newsletters

Aggregate content from niche blogs, industry publications, and thought leaders into a single dataset. Use as the data source for automated newsletter generation or content recommendation systems.

🔍 Competitive Intelligence

Subscribe to competitor blogs, press release feeds, and industry news. Get structured alerts when new content is published. Combine with keyword filtering for targeted monitoring.

📊 Research & Dataset Building

Build timestamped article datasets for NLP research, media studies, or training data collection. The consistent schema makes downstream processing straightforward.

🤖 AI Pipeline Input

Use as a data source for LLM-powered summarization, classification, or knowledge base updates. The structured output integrates directly with vector databases and RAG pipelines.

⏰ Scheduled Monitoring

Run on a schedule (hourly, daily) with Apify's scheduling feature. Combine with deduplication logic downstream to maintain a continuously updated article database.

Technical Notes

• Uses Python stdlib xml.etree.ElementTree for XML parsing (no lxml dependency)
• HTTP requests via httpx with async support and configurable timeouts
• Handles BOM-prefixed feeds and common encoding edge cases
• Date parsing supports RFC 822 (RSS) and ISO 8601 (Atom) formats
• Full content extraction removes <script>, <style>, and <noscript> blocks before stripping HTML

Pricing

$0.0005 per article parsed and pushed to the dataset.

Example Feeds to Get Started

🔗 More Scrapers by Ken Digital

👉 View all scrapers

🔗 Quick Integration

Python

from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("joyouscam35875/rss-news-aggregator").call(run_input={...})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)

Node.js

import{ ApifyClient }from'apify-client';
const client =newApifyClient({token:'YOUR_API_TOKEN'});
const run =await client.actor('joyouscam35875/rss-news-aggregator').call({...});
const{ items }=await client.dataset(run.defaultDatasetId).listItems();

No-code: Make / Zapier / n8n

Search for this actor in the Apify connector. No code needed.