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TaskHandoff
TaskHandoff

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TaskHandoff: one console for AI coding workspaces across local and remote machines

If you run AI coding sessions (Codex, agents, background jobs) for more than a few weeks, they start to sprawl. One session on the laptop, one on a home server, a couple inside Docker containers on a remote VM — and no single place that tells you what is running, where it lives, and how to hand it off.

TaskHandoff is an open-source control plane (Apache-2.0, TypeScript) that pulls those AI workspaces into one board. I've been using it to keep local and remote machines in the same view, and it's finally at a state worth sharing.

The problem

Once AI sessions spread across machines, you end up juggling:

  • SSH tabs, container shells, and a half-dozen config files
  • No shared view of "what's running where"
  • Rebuilding the same container toolchain over and over
  • Copy-pasting context between a chat app and the machine that actually does the work

What it does

  • Multi-node management — local and remote machines in a single board
  • Managed Docker workspaces — create, run, and restore workspaces as first-class objects
  • Environment templates — snapshot a container's tools + config and reuse it elsewhere
  • AI session center — real-time sessions over WebSocket, attach/detach at will
  • Repository workflows — files, changes, branches, and git worktrees from the UI
  • Scoped Git credentials — hand each workspace only the credentials it needs
  • Chat integrations — route tasks from Telegram, DingTalk, WeChat, or Lark
  • App catalog + mobile client — plus a Desktop app and a server, with an English/Chinese UI

Quick start

curl -fsSL https://github.com/edgestorage/task-handoff/releases/latest/download/install-server.sh | sudo sh
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Ships as a Desktop client and a server (systemd on Debian/Ubuntu). Once the server is up, open the console and add your machines.

Why it exists

Most AI tooling optimizes the model. TaskHandoff optimizes the plumbing — the boring, error-prone part of running those models somewhere real, across more than one box, without losing track of your sessions.

Links

Apache-2.0. Stars, issues, and PRs are all welcome — and I'd love to hear how you're juggling multi-machine AI sessions today.

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