Glanced is an aggregator-style RSS reader focused on bringing all the content a user follows together in one place. According to the official introduction, it can be used to follow news, blogs, newsletters, and podcasts, with the goal of unifying content scattered across different platforms into a single library so users can catch up on the day's updates in one scroll.
[Main purpose] Glanced is aimed at users who want to stop switching between multiple apps and websites and have content come to them. The official slogan emphasizes "Everything You Follow, At a Glance" and "Stop chasing content. Let it come to you." That is, subscribe to the sources you follow and let the reader present them in one place.
[Main capabilities]
- Content aggregation: Websites, blogs, newsletters, and podcasts exist side by side in the same library, and users can complete the day's reading in a single scroll.
- AI summaries: Key points can be generated for any article in seconds, helping users judge the value of the content before deciding whether to read further.
- Full-text fetching: Glanced fetches complete articles so users can read the full text instead of truncated previews.
- Story aggregation: Reports on the same event from different sources are grouped into one story with an automatically drafted title, presenting multi-angle coverage while reducing duplicate content.
- Related reading: While users read, articles related to the current content are presented.
- Newsletter delivery: Newsletters enter Glanced as articles instead of piling up in the inbox.
- Browser extension: Detects feeds on any web page and subscribes automatically.
- Podcast listening: Can be done side by side with reading in the same app, without opening a separate podcast app.
- Discovery catalog: Browse hundreds of media outlets and thousands of podcasts and subscribe without pasting a URL.
- Organization features: Use folders to categorize subscriptions, use tags to mark articles for later retrieval, set content as read later and continue on any device.
- Search: Search every article in the library and find it instantly; while reading, Glanced suggests related tags to speed up organization.
- Smart subscriptions: Save complex queries as smart feeds that can be run repeatedly.
- Keyboard shortcuts: Quickly browse the library without using a mouse.
- Migration: Switch from other readers and bring your existing subscriptions with you.
- Sharing and integrations: Send articles to the apps users already use; in addition, it also provides API, webhooks, and MCP server, for users who want to build their own.
- Native apps: The official statement says the native apps let you take your library with you and continue from where you left off across different devices.
[How to use] The information given on the official page includes: a free 14-day trial with no credit card required; detecting website feeds via a browser extension; browsing media and podcasts in a discovery directory and subscribing; grouping subscriptions into folders; tagging articles, setting them to read later, and saving searches as smart feeds; using keyboard shortcuts; importing subscriptions from other readers; sending articles to other apps; and building your own via API, webhooks, and MCP server. The page does not provide specific step-by-step tutorials, pricing plans, platform support scope, or other details.
[Use cases] Suitable for users who follow multiple news sites, blogs, newsletters, and podcasts at the same time and want to reduce repeated browsing and quickly filter content worth reading; it is also suitable for users who need to continue reading across devices, manage a large number of subscriptions with tags and folders, or want to extend their workflow on their own via API and webhooks.
[Limitations and information not yet provided] The official page shows a 14-day free trial with no credit card required, but it does not explain the billing method or price after the trial period ends. The page does not provide details such as the specific list of supported platforms and devices, the model used for AI summaries, the success rate range for full-text extraction, API quotas or call limits, or the specific method for connecting the MCP server. The above content is not yet provided and should be subject to later official statements.
