What is Local Operator?

Local Operator is an agent runtime that runs on your machine. You hand it a task the way you would to someone sitting at your desk — sort this folder, find what broke in last night's build, pull the numbers out of these invoices — and it works: running commands, editing files, reading the web, asking for approval before anything risky.

It is open source (MIT), and it does not need a cloud account. Your sessions, credentials and configuration live in ~/.local-operator/ on your computer, and model calls go to whichever provider you signed in to.

One install is one pool of sessions, and several front ends drive it:

• Terminal. lop opens a full-screen TUI: streaming transcripts, expandable tool cards, an approval prompt before anything writes.
• Desktop app. A window for the same work — chat with run details, projects, schedules, a browser, and the Agent hub.
• Phone. The mobile relay lets you watch, steer, or start sessions from your phone, against the machine doing the work.
• Browser extension. The agent gets the browser you are already signed into — its own tab, your logins, your permission per site.
• Headless. lop exec "..." runs one task with no interface at all, ready for scripts, cron, and CI.
• Python SDK. local_operator.sdk embeds the runtime in your own Python code.

Sessions are shared, not siloed: a conversation started in the terminal shows up in the desktop app's list, the sidebar, and the phone relay — because all of them read the same local session store.

• It runs on your machine. Commands execute on your computer, edits land in your files, and nothing runs on servers we control — because there are none. Your provider credentials stay local.
• Teams, not one-off prompts. A team is a manager plus members (reviewer, coder, architect, designer, and more) with a written brief. You hand over a goal; the manager splits it, delegates, and reports back.
• Projects. Durable workstreams gather related sessions, milestones and progress in one place, so work that spans days or several conversations keeps its shape.
• The mesh. Pair your computers and they can see each other's sessions: start one on the always-on box, prompt it from the laptop, and move a conversation between machines — transcript and all — when you move.

• Work continues when you walk away. Sessions schedule their own future turns, and a small supervisor wakes them even if the terminal that scheduled the work is long closed. Aida, the built-in chief of staff, checks in once a day with what needs your attention.
• Bring your own models. Sign in to the subscription you already pay for (Claude, ChatGPT, Kimi, Grok, Z.AI, Qwen), use an API key, or point it at a local model with LM Studio, Ollama, vLLM or llama.cpp.

• Not a cloud service. There is no Local Operator cloud, and no remote account holding your sessions. When all your machines are off, nothing runs.
• Not a model. It does not ship weights and does not charge for model use — you bring a provider or a local model, and you pay that provider directly.
• Not autopilot. Read-only tools run on their own, but anything that writes files or runs commands asks first until you decide otherwise.
• Not only for code. The same agent does research, file work, data cleanup and scheduled jobs — coding is just where it starts.