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NoteTrace is a self-hosted alternative to Google Keep, Evernote and Apple Notes: notes, checklists and reminders in a card grid, on your own server. AGPL-3.0, a single Docker container, a web app that works offline, a native Android app, and a Wear OS app. No telemetry, no cloud. This is the first stable release.
Part of the TraceApps family: NutriTrace (nutrition), CookTrace (recipes / pantry / shopping), LiftTrace (strength / lifting).
What it does
- Notes and checklists. Pins, colors, nested labels, archive, trash, version history, and full-text search that also finds words in voice transcripts and in photos.
- Reminders and Tasks. Repeating reminders that keep their local time, exact alarms on Android, and one view of everything that's due.
- Offline everywhere. The installed web app keeps editing with no connection and syncs later; Android and the watch work offline too.
- Wear OS. Tick off lists, read notes, see what's due, and speak a note ("call the plumber tomorrow at nine" sets the reminder), with a tile and a watch face complication.
- Voice notes and drawings. Record with the screen off and get a transcript you can tap to jump to.
- Bring your notes with you. Import from Google Keep, Evernote, Memos, Blinko and Markdown vaults; export everything as Markdown with images.
- Optional AI. Tidy up, summarise, or turn a note into a checklist, with the provider of your choice. Off unless you set it up.
Links
- Repo: https://github.com/TraceApps/notetrace
- Docs: https://traceapps.github.io/docs/notetrace/
- Release notes + signed APKs (phone and watch): https://github.com/TraceApps/notetrace/releases/tag/v1.0.0
- Docker:
ghcr.io/traceapps/notetrace:latest(mirror:traceapps/notetrace:latest)
AI Disclosure
Per Rule 7 / [AIP] disclosure requirements AI was used during development as a coding assistant. Level per category:
- Design (architecture, system design): Hint: I make the architectural calls; AI suggests trade-offs and edge cases I might have missed.
- Implementation (production code): Pair: roughly 50/50. AI drafts, I review, adjust, test on real hardware, and only commit what I've verified. Every commit is manually reviewed before it goes to my dev repo.
- Testing (writing tests, test plans, QA): Assisted: real-device testing is manual (I test on my own PC and mobile devices before every release). AI helps draft test plans and think through edge cases.
- Documentation (docs, comments, README, CHANGELOG): Pair: release notes and changelog entries are drafted with AI then edited for tone; comments and code docs are mostly Pair as well.
- Review (code review, PR feedback): Assisted: I'm the reviewer; AI helps with security sweeps, audit passes on complex changes, and consistency checks.
- Deployment (CI/CD config): Hint: Docker/GitHub Actions/release pipeline is largely conventional; AI-suggested improvements only.
Glad you are liking it so far! Yes i have thought about adding Kanban support, but i am not sure if its the right fit to implement in the app. Will surely continue to think about and consider it for the future! I've been thinking about putting all my apps on F-Droid, so i will say coming soon!. With respect to the color... you can change it to literally whatever you want in Settings under Apperance, so you are not stuck to the purple if you prefer something else.