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RSS filter

Free

Clean your RSS feeds by filtering out noise

LLM ModelsFreeFree tier
Type
Saas
Company
RSS Filter

About RSS filter

RSS Filter is a recommendation system based on user read articles. It replaces the original RSS feed URLs with a backend URL to filter out unwanted items and track user read articles. It uses LLM embeddings and machine learning to recommend similar articles. Users can convert existing feeds by uploading an OPML export from their RSS client.

How to Use

Upload an OPML file exported from your RSS client to automatically convert your existing feeds. The system will then filter unwanted items and recommend similar articles based on your reading history.

RSS Filter's

Key Features

  • Filters unwanted items from RSS feeds.
  • Tracks user read articles.
  • Recommends similar articles using LLM embeddings and machine learning.
  • Supports OPML import for easy feed conversion.

Use Cases

  • Filtering out irrelevant content from RSS feeds to focus on desired topics.
  • Discovering new articles similar to those already read and enjoyed.
  • Managing and organizing RSS feeds more efficiently.

Key Features

Filters unwanted items from RSS feeds.
Tracks user read articles.
Recommends similar articles using LLM embeddings and machine learning.
Supports OPML import for easy feed conversion.

Pros & Cons

Pros
  • Completely free with no hidden costs
  • Simple and intuitive interface – just paste a URL and add filters
  • Open-source, allowing self-hosting and community contributions
  • Effectively removes clutter without requiring a full reader switch
Cons
  • Currently only filters by keywords/categories – no advanced ML-based recommendations
  • Requires a public RSS feed URL; does not integrate directly with RSS reader apps
  • No support for filtering by author, date, or other metadata

Best For

Filtering out irrelevant content from RSS feeds to focus on desired topics.Discovering new articles similar to those already read and enjoyed.Managing and organizing RSS feeds more efficiently.

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