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I built an open-source AI coworker that logs in with 2FA without the model ever seeing your passwords

A developer has released Godmode Bot, an open-source (MIT) AI coworker that pairs a real browser with stored logins and 2FA codes while keeping those secrets hidden from the underlying model. Built with Tauri 2 and using Claude Code as its reasoning engine plus browser-use to drive a managed Chromium, it supports macOS, Windows, Linux and headless server deployments, with per-agent git repositories that log every run and can be rolled back. Credentials are injected into pages over CDP via vault_fill_login and vault_fill_totp tools, and the project ships a SECURITY.md threat model and Docker Compose setup.

by read2 min views1 publishedSep 27, 2026

Every AI agent I tried had the same weak spot: it was great until it reached a login screen. Then it needed a password, a 2FA code, or me.

So I built Godmode Bot, an open-source (MIT) AI coworker that has a real browser plus your logins and 2FA codes. The model never sees any of those secrets.

Godmode Bot is a desktop app for macOS, Windows and Linux built with Tauri 2. It can also run headless on a server, NAS or Raspberry Pi with a web dashboard. It uses Claude Code as the brain and browser-use to drive a managed Chromium.

You can start with a single chat ("log into our billing portal and download September's invoice"), or build a team of persistent agents that each have their own instructions, memory, schedules and history.

This is the part I spent the most time on.

vault_fill_login or vault_fill_totp. Godmode types the value into the page over CDP. Getting secrets in is easy too. You can import passwords from Chrome, 1Password, Bitwarden, Apple Passwords or Firefox, and 2FA from a screenshot of a Google Authenticator export QR code (multi-account codes work).

Every agent gets its own repository:

~/.godmode/agents/invoice-collector/
├── CLAUDE.md                 # identity & instructions
├── MEMORY.md                 # long-term memory the agent maintains
├── conversations/<id>.md     # transcripts
├── runs/2026-09-27/<id>.jsonl# raw event logs (secrets redacted)
└── workspace/                # files the agent produced

Every run is committed, so you can see exactly what an agent learned and did, and roll it back.

Each turn runs claude -p --output-format stream-json inside the agent's git repo and streams every thought, tool call and screenshot to the UI. A local MCP gateway gives the agent vault tools, delegation tools and report_missing_login. You can watch the browser live next to the chat and take control at any point, for example to solve a CAPTCHA.

Agents run Claude Code with bypass permissions, so there are no permission prompts. Treat it like a trusted coworker with access to your machine. For sensitive setups, run it in a VM or container. SECURITY.md covers the threat model.

docker compose up -d and open I'd love feedback, especially on the vault design and what you'd want agents to do next. A full computer-use VM mode is on the roadmap.

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