Your mail, connected.
Sign in to Gmail in your browser, or connect an IMAP account.
Your provider. Your account.A calmer inbox starts in your terminal
Meet Inboxed. Organize your email with AI running on your computer, review what it suggests, and make room for what matters.
A little room to breathe.
A WORKSPACE WITH SOME BREATHING ROOM
Categories, topic tags, and a review queue, brought together in one terminal workspace. Start with a small scan and take it from there.
$ inboxed scan --limit 3
Scan complete. Your mailbox is unchanged.
Illustrative preview. Example messages, real workflow.
LESS SORTING. MORE LIVING.
A simple rhythm for the email you want to keep, the clutter you want to clear, and everything in between.
Sign in to Gmail in your browser, or connect an IMAP account.
Your provider. Your account.Run a local Ollama model to classify messages into your categories and optionally suggest topic tags. Scans save proposals for review.
AI running on your computer.Review, edit, approve, or reject suggestions. Apply labels, archive, or move messages to Trash when you’re ready. Automation is an explicit choice.
Review first. Apply when ready.Email content goes to your local Ollama instance for classification and optional tags. Inboxed has no hosted mailbox backend.
Tokens, scan history, message metadata, and previews stay in your local app data. You control their retention.
Read the code, understand the permissions, and choose your own categories.
A FRESH START, ONE COMMAND AWAY
You’ll need Python 3.13+, uv, and a running local Ollama instance with a compatible model. The README covers model setup and configuration.
Read the setup guidegit clone https://github.com/marvalkrystof/inboxed.git
cd inboxed
uv sync --extra tui
uv run inboxed init
uv run inboxed tuiOpen the Accounts tab to connect, then scan and review.
BUILT IN THE OPEN
Inboxed is maintained by Kryštof Marval. Find documentation, report a problem, or help shape the project on GitHub.