Documents and notes decision

NewsBlur

Self-hosting is practical and supported by the project's MIT-licensed repository; a technical user should self-host or run the hosted plan depending on desired scale and managed features.

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Subscription$3/month ✓ verified
Initial build6 hours
Monthly upkeep4 hours + $0
Evidence2/2 runs agree

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.

What a replacement has to do

  • Fetch feeds and pages, extract full text, index stories for search, present synced reading UI with training/classifiers, and run background fetcher to keep feeds updated.

What it still won’t have

  • Hosted scaling and high-frequency managed fetch fleet (5–15 minute Pro fetching)
  • Managed push notifications and mobile-store distributed apps (hosted updates/support)
  • Priority support and SLA
  • Hosted AI integrations (Ask AI / Daily Briefing) unless you wire your own model/API and pay separately

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying

Subscription price × seats × 12

Build it

AI build APIs + hosting

Time you would spend

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hostable RSS/news reader based on Python/Django + Postgres + Redis + OpenSearch, containerized with Docker Compose. In scope: implement a feed fetcher worker that handles RSS/Atom and web-page change detection, a readability-based full-text extractor, story storage schema, search indexing and backfill, a minimal web UI for login, subscription management, folders, river-of-news folder stream, story views (list, split, text, original), basic training (thumbs up/down per author/title/tag) stored per-user and applied to highlight/fade stories, OPML import/export, and a Docker Compose setup to run web, worker, redis, db, and OpenSearch. Out of scope: native mobile apps, managed push notification infrastructure, and proprietary AI integrations (Ask AI). Require error handling for fetch failures and extractor edge-cases, unit tests for fetcher, extractor, and API endpoints, and an integration test that boots all containers and performs an OPML import + fetch cycle.
How we checked5 sources · 2/2 runs agreed · evidence score 99

How the score was reached

  • Self-host verdict base92
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • 2/2 assessment runs agreed+4
  • Evidence score99

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.

How scoring works →

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 2 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded