ClipNews API

API Access to high quality news summaries

Our ClipNews API provides access to high-quality news summaries from various sources. Stay updated with the latest news across different categories, all conveniently summarized for quick consumption. Perfect for developers, researchers, and businesses looking to integrate up-to-date news content into their applications or workflows.

ClipNews API Illustration
Some Tailored Sources

High Quality News Sources

Get Smarter News Data

Comprehensive insights with global reach. Our service scans and summarizes thousands of articles daily, providing you with a clear, concise view of the world's news. Stay informed with AI-powered news discovery and search, including advanced embedding search and automatic recommendations.

API Example
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Newest Articles

ClipNews collects the latest news from different sources all over the internet.

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Search

Search for articles by keyword, category, embedding, time range, and much more.

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Archive

The ClipNews archive has all relevant news articles beginning december 2023

High Quality News Articles

ClipNews provides cleaned, filtered articles which have been enriched with images, semantic entities, summaries and vector embeddings.

Vector embeddings can be used to find articles based on similar concepts. For example searching for `car` will also return articles about `automobile` and `vehicle` or `SUV`.

API Example
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Metadata

ClipNews enriches articles with high quality metadata to make them as useful as possible for your intended usecases.

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Entities Search

You can also find articles by a particular entity. To see all known ClipNews entities, there's a entity search endpoint.0'

Article Recommendations

Do you want to find the best articles based on a users interest? The recommendation endpoint accepts articles a user liked (or clicked or viewed) and articles a user didn't like (or downvoted). Based on this, you will receive the articles this user most likely will like (out of all the articles of the past 24 hours.

No need to build your own recommendation engine.

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Embeddings

Recommendations are based on vector embeddings, to provide the best possible results.