I Built a CLI for Proton Mail, Drive, Calendar, Pass and Contacts

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I made a command line tool for Proton. It covers Mail, Drive, Calendar, Pass and Contacts. It is one static binary for Linux, macOS and Windows. Proton doesn't have a CLI for all their web interfaces. There is one for Drive and one for Pass, but the other ones are not really there. There's no Mail CLI, Contacts or other CLIs. I wanted to have everything in one. It does logins the way the Proton apps do, with SRP. It decrypts and encrypts on your machine with Proton's own Go libraries, go-srp and gopenpgp. Your password never leaves the machine. It talks to the same API as the Proton web apps. There is no bridge and no daemon. It runs one command and exits. Some things it can do: proton mail messages list --unread proton mail messages get "Invoice #2291" proton drive items upload ./report.pdf /Documents proton calendar events list proton pass items totp github.com Every command has the same shape: proton <app> <collection> <verb>. Every command can print JSON. Every command that changes something takes --dry-run. This CLI does things the web interfaces do, in those five apps. But some things need a browser and are not here: importing from Gmail, adding a Zoom link, registering a security key and so on. VPN, Wallet, Docs, Meet, Lumo and Authenticator are not covered. Most of the code was written with LLMs as you can see. But I have an extensive test suite: 397 live tests against three real Proton accounts and a record of the 243 API endpoints they reach. Install with curl, Homebrew, winget, APT, AUR, Nix, npm or take a binary from the releases page. Feedback is more than welcome :)

Visit product View on Hacker NewsSep 13, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, apps · Missing: agents, agent, cursor

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: vpn · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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