agent-computer

npx skills add FrancoAA/agent-computer

Give any coding agent its own Linux desktop: a Docker container with XFCE, Chromium, Blender, LibreOffice, GIMP, a shell with sudo, and your project folder at /workspace. You can watch it live in your browser.

It isn't tied to one agent. The same computer can be used three ways:

Install as a skill (recommended)

npx skills add FrancoAA/agent-computer installs it for Claude Code, Codex, pi, Cursor and other agents (add -g for all projects). Manual alternatives:

The skill folder skills/agent-computer/ is self-contained: SKILL.md, a single bundled CLI (scripts/agent-computer.mjs, no npm install needed) and the Dockerfile. Requirements: Docker and Node.js 20+.

node skills/agent-computer/scripts/agent-computer.mjs install-skill all   # Claude Code, Codex (~/.agents), pi
# or one target: install-skill claude | codex | pi | agents | <folder>

Or unzip release/agent-computer-skill.zip (npm run pack:skill) into any of:

Claude Code can also install it as a plugin: /plugin install agent-computer --marketplace FrancoAA/agent-computer (Claude Code 2.1.275+).

On first use the skill builds the desktop image in the background (~10 minutes, ~9 GB) and tells the agent to retry; agent-computer image status shows progress.

Sandboxed agents: the CLI needs the Docker socket. Codex's workspace-write sandbox blocks it, so Codex asks you to approve running agent-computer commands outside the sandbox (non-interactive codex exec can't, and reports that clearly).

Skills that run on hosted sandboxes (claude.ai, the API's code execution) won't work: they have no Docker.

Related MCP server: Qubicl

Install the CLI (for MCP and run-inside)

npm install && npm run build && npm link     # `agent-computer` on your PATH (bundled CLI)
agent-computer image build                   # optional: build the image now instead of on first use
agent-computer up && agent-computer view     # start it and watch the desktop
agent-computer setup claude                  # MCP: claude | codex | pi; `setup cursor` prints the JSON

T3 Code runs Claude Code and Codex with their own configs, so the skill or setup claude / setup codex covers T3 sessions too. To run an agent entirely inside the computer from T3 Code (or Zed, or Open Codex), add a custom ACP agent with command agent-computer and arguments run -- claude-agent-acp (or run -- codex-acp, or run -- cursor-agent acp with a Cursor-enabled image).

MCP tools

computer_info, screenshot, click, move_mouse, drag, type_text, press_keys, scroll, shell, open (URL or GUI app), list_windows, focus_window, read_file, write_file, view_image, blender (headless bpy scripts and renders).

For DOM-level browser automation, add Playwright's MCP server attached to the computer's Chromium: claude mcp add agent-computer-browser -- agent-computer browser-mcp.

Which computer?

One per project folder by default (named after the folder), so agents in different repos don't share a desktop. Override with --name NAME or AGENT_COMPUTER=NAME. The project folder is shared at /workspace, except $HOME and /, which get a private volume instead (also forced with --no-workspace).

agent-computer list
agent-computer --name blender-lab up --gpu --cpus 8 --memory 16g
agent-computer --name blender-lab destroy

--gpu shares /dev/dri (Mesa/AMD/Intel) for hardware-accelerated Blender viewports and EEVEE.

Running agents inside

run copies the matching host login into the computer (~/.claude/.credentials.json, ~/.codex/auth.json, Cursor's auth.json, Gemini's OAuth file), forwards common API-key variables, and passes stdio through. Interactive TUIs get a TTY; Ctrl-C goes to the agent. When the caller stops run (SIGTERM/SIGHUP), the agent's whole process group is killed inside the container.

The image includes Claude Code, Codex, claude-agent-acp, codex-acp and Playwright MCP. Cursor's agent CLI is only distributed as a remote install script, so it is opt-in: build with AGENT_COMPUTER_WITH_CURSOR=1 agent-computer image build.

Security model

• This is a container, not a VM: it shares the host kernel. It contains mistakes and sprawl well; it is not a hard boundary against a hostile workload. For stronger isolation install gVisor or Kata Containers and set AGENT_COMPUTER_RUNTIME=runsc (or kata-runtime); new computers then start under that runtime.

• The shared /workspace folder is read-write. Use --no-workspace for a fully private computer.

• Logins copied in with run/auth are readable by anything running inside the computer.

• The desktop (noVNC) and DevTools ports are bound to 127.0.0.1 on random ports and have no password. Anyone with access to your machine's localhost can view and control the desktop.

• No Docker socket is mounted, and the container is not privileged. The agent has sudo inside the container.

How it works

skills/agent-computer/docker/ builds a Debian trixie image. Its entrypoint starts Xvfb (:1), an XFCE session, x11vnc (container-local) and noVNC on port 6080, plus a relay for Chromium DevTools on 9223. The CLI talks to Docker directly: docker exec + xdotool/scrot for input and screenshots, docker cp for files, and docker exec -i with a per-command process group for run/exec.