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Open Computer Use

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iFurySt
open-computer-use

Platform-neutral guidance for using Open Computer Use, the open-source Computer Use MCP server and CLI for macOS, Linux, and Windows. Use when an agent needs to install, verify, troubleshoot, configure, or operate Open Computer Use through its native CLI, stdio MCP server, or direct Computer Use tool calls.

Overview

PublisheriFurySt
Repositoryopen-computer-use
Skill nameopen-computer-use
Stars
2.7K
Forks
250
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by iFurySt on GitHub. Read the source before you install it.

Installation

Install the Open Computer Use AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/iFurySt/open-computer-use/tree/main/skills/open-computer-use
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/iFurySt/open-computer-use.git /tmp/open-computer-use
mkdir -p .claude/skills
cp -r /tmp/open-computer-use/skills/open-computer-use .claude/skills/open-computer-use
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Open Computer Use in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Open Computer Use on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Open Computer Use is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Open Computer Use

Overview

Open Computer Use exposes Computer Use as a local CLI and stdio MCP server. It is not Codex.app-specific; adapt the commands and MCP config to the agent runtime you are operating in.

The macOS runtime requires macOS 14.0 or later. Windows and Linux use their own platform runtimes and are not subject to this macOS minimum.

It supports the same core tool surface across macOS, Linux, and Windows: list_apps, get_app_state, click, perform_secondary_action, scroll, drag, type_text, press_key, and set_value.

The macOS runtime additionally implements select_text, which selects the given text inside a text element or places the text cursor before / after it (selection: text, cursor_before, cursor_after). Pass text exactly as it appears in the accessibility tree, plus prefix / suffix when it is not unique; an ambiguous target fails closed instead of silently selecting the first match. JavaScript exposes app.selectText(elementIndex, text, options?). Unreadable or mismatched range verification throws, including when full action read-back is off. Windows and Linux runtimes do not implement this tool yet.

macOS additionally exposes query: a targeted accessibility lookup that finds controls by text and/or role without rendering a tree or taking a screenshot.

Core Workflow

  1. On macOS, run sw_vers -productVersion before invoking the CLI and require macOS 14.0 or later. On older versions, explain that the runtime cannot launch; do not recommend doctor or permission changes as a fix for binary incompatibility.
  2. Check the CLI is installed with open-computer-use -h or ocu -h. If installation or setup is missing, read references/installation.md.
  3. On supported macOS versions, run open-computer-use doctor before the first real GUI task. If permissions are missing, ask the user to approve Accessibility and Screen Recording in the onboarding UI.
  4. Inspect available apps before acting: open-computer-use call list_apps.
  5. Capture current UI state with open-computer-use call get_app_state --args '{"app":"TextEdit"}'. The default state is usually enough for UI operation.
  6. When the task needs longer semantic text, such as chat history, email bodies, document text, or long form content, call get_app_state with text_limit: 1000 or text_limit: "max".
  7. When visible long pages or lists appear incomplete even after scrolling, call get_app_state with a larger max_tree_nodes or max_tree_depth.
  8. Prefer element-targeted actions using element_index from the latest get_app_state result.
  9. For multi-step CLI work, use open-computer-use call --calls '<json-array>' so one process can reuse the latest element index mapping.
  10. For agent runtimes that support local MCP servers, configure open-computer-use mcp or ocu mcp and call the exposed Computer Use tools directly. Read references/usage.md.
  11. For direct code-first orchestration, run ocu capabilities and then use one-shot ocu js or persistent ocu repl. Read references/usage.md.
  12. If communication, permission, or desktop-session access fails, read references/troubleshooting.md.

Operating Rules

  • Treat the target desktop as the user's real session. Do not inspect password managers, unrelated private content, or sensitive apps unless the user explicitly asked for that task.
  • Ask before sending, deleting, purchasing, approving, uploading, or making other externally visible changes.
  • Do not assume Codex.app plugin helpers are available. Use the installed open-computer-use / ocu CLI or an explicit MCP config.
  • Use indexes returned by get_app_state or macOS query in the same native session; do not guess indexes across sessions or after large UI changes.
  • Prefer semantic actions and set_value for editable controls. Use coordinate click, scroll, and drag only when the element tree does not expose a safer target.
  • On macOS, do not enable OPEN_COMPUTER_USE_ALLOW_GLOBAL_POINTER_FALLBACKS=1 unless the user explicitly requested click_method: "global", a drag that must drive a window-server drag session (window move, drag-select text, Finder drag-and-drop), or other diagnostic behavior that may move the real pointer. Without it drag reports Drag delivered via app_post and those operations have no effect; see references/usage.md for alternatives.
  • On Windows and Linux, confirm the command is running inside the logged-in desktop session before assuming GUI automation is available.

Common CLI Actions

sh
open-computer-use -h
ocu -h
ocu capabilities --json
ocu js 'nodeRepl.write(6 * 7)'
ocu repl
open-computer-use doctor
open-computer-use call list_apps
ocu call list_apps
open-computer-use call get_app_state --args '{"app":"TextEdit"}'
open-computer-use call get_app_state --args '{"app":"TextEdit","text_limit":1000}'
open-computer-use call get_app_state --args '{"app":"TextEdit","text_limit":"max"}'
open-computer-use call get_app_state --args '{"app":"Google Chrome","max_tree_nodes":3000,"max_tree_depth":96}'
open-computer-use call click --args '{"app":"TextEdit","element_index":"0"}'
open-computer-use call type_text --args '{"app":"TextEdit","text":"Hello from Open Computer Use"}'

For a short sequence that reuses state in one process:

sh
open-computer-use call --calls '[
  {"tool":"get_app_state","args":{"app":"TextEdit"}},
  {"tool":"press_key","args":{"app":"TextEdit","key":"Return"}}
]'

MCP Usage

For runtimes that can launch local MCP servers over stdio, use:

toml
[mcp_servers.open_computer_use]
command = "open-computer-use"
args = ["mcp"]

Read references/usage.md for JSON config examples, direct tool-call patterns, and platform notes.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Open Computer Use AI skill do?

Platform-neutral guidance for using Open Computer Use, the open-source Computer Use MCP server and CLI for macOS, Linux, and Windows. Use when an agent needs to install, verify, troubleshoot, configure, or operate Open Computer Use through its native CLI, stdio MCP server, or direct Computer Use tool calls.

Why use Open Computer Use on TypingMind?

Because you install it once and use it with any model. Open Computer Use is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Open Computer Use in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/iFurySt/open-computer-use/tree/main/skills/open-computer-use. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Open Computer Use?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Open Computer Use?

As many as you like. As long as a model supports skills, you can use Open Computer Use with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Open Computer Use AI skill free?

Yes. It is published on GitHub by iFurySt under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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