Open Computer Use
An MCP service for running desktop Computer Use operations from AI clients.
What does this agent do, and when should you use it?
Open Computer Use is an open-source Computer Use service packaged as an MCP server. It is documented to let AI agents and MCP clients run Computer Use on macOS, Linux, and Windows. The npm package provides the open-computer-use command and the ocu alias, plus installers for Codex, Claude Code, Gemini CLI, and opencode configuration. Its CLI can invoke one tool or execute a sequence in one process so element_index state can be reused, printing MCP-style JSON results. The macOS runtime requires macOS 14.0 or later and requires Accessibility and Screen Recording permissions on first use.
The service is started with open-computer-use or ocu and exposed to clients with the open-computer-use mcp command. Documented calls include list_apps, get_app_state with an app argument such as TextEdit, and press_key with app and key arguments. open-computer-use call executes one Computer Use tool and prints an MCP-style JSON result. The --calls and --calls-file options execute multiple tool calls in one process, allowing element_index state to be reused. Built-in install commands write MCP configuration for Codex, Claude Code, Gemini CLI, or opencode.
- A Codex App or Codex CLI user who wants to connect a local Computer Use service through MCP.
- A Claude Code user who needs install-claude-mcp to add the service to ~/.claude.json.
- A Gemini CLI user working in a project who wants to write the integration to ./.gemini/settings.json.
- An opencode user who wants the MCP server added to ~/.config/opencode/opencode.json or the active configuration file.
- A desktop automation user who needs to inspect TextEdit and then send Return in one reusable-state call sequence.
What are this agent's strengths and limitations?
- It exposes Computer Use through MCP, and the documentation states that any AI agent or MCP client can use it.
- It explicitly documents macOS, Linux, and Windows support and includes demonstrations for the platforms.
- Built-in installers target Codex, Claude Code, Gemini CLI, and opencode rather than requiring every integration to be written by hand.
- Sequence execution through --calls or --calls-file preserves element_index state within one process.
- Single CLI calls print MCP-style JSON, which is useful for inspecting scripted tool invocations.
- The macOS runtime is limited to macOS 14.0 or later and requires Accessibility plus Screen Recording permissions on first use.
- Client setup changes user or project configuration files, including ~/.codex/config.toml, ~/.claude.json, and ./.gemini/settings.json.
- The supplied material shows only a few callable tool examples and does not provide a complete tool catalog or failure-result schema.
- The supplied material does not detail permissions, desktop-environment assumptions, or dependencies for Windows and Linux.
- No hosted offering, SLA, or commercial support is described in the supplied material.
How do you install or deploy this agent?
Install globally: npm i -g open-computer-use. Start it with open-computer-use or ocu. On macOS, the runtime requires macOS 14.0 or later; run it once and grant Accessibility and Screen Recording permissions. For Codex, run open-computer-use install-codex-mcp. Manual MCP configuration is: {"mcpServers":{"open-computer-use":{"command":"open-computer-use","args":["mcp"]}}}.
How do you use this agent?
Start open-computer-use, then connect an MCP client to command open-computer-use with args ["mcp"]. Test a tool call with open-computer-use call list_apps. Query an application with open-computer-use call get_app_state --args '{"app":"TextEdit"}'. Run a sequence with open-computer-use call --calls '[{"tool":"get_app_state","args":{"app":"TextEdit"}},{"tool":"press_key","args":{"app":"TextEdit","key":"Return"}}]'.
How does this agent compare with similar options?
The project says it was inspired by OpenAI Codex Computer Use and demonstrates use in Codex App and Codex CLI, describing the experience as matching the official one. Its documented delivery model is a locally installable open-source MCP service; the supplied material does not provide a detailed feature-by-feature comparison.