by deedy · Agent Tool · ★ 846
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Anthropic Computer Use (for Mac) Anthropic Computer Use is a beta Anthropic feature which runs a Docker image with Ubuntu and controls it. This fork allows you to run it natively on macOS, providing direct system control through native macOS commands and utilities. [!CAUTION] This comes with obvious risks. The Anthropic agent can control everything on your Mac. Please be careful. Anthropic's new Claude 3.5 Sonnet model refuses to do unsafe things like purchase items or download illegal content. Features Native macOS GUI interaction (no Docker required) Screen capture using native macOS commands Keyboard and mouse control through cliclick Multiple LLM provider support (Anthropic, Bedrock, Vertex) Streamlit-based interface Automatic screen resolution scaling File system interaction and editing capabilities Prerequisites macOS Sonoma 15.7 or later Python 3.12+ Homebrew (for installing additional dependencies) cliclick () - Required for mouse and keyboard control Setup Instructions Clone the repository and navigate to it: Create and activate a virtual environment: Run the setup script: Install Python requirements:
| Stars | 846 |
| Forks | 134 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 44.25/100 |
| Open Issues | 16 |
| Last Updated | 2024-12-16 |
| Created | 2024-10-24 |
| Platforms | claude-code, python |
| Est. Tokens | ~6k |
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mac_computer_use is A fork of Anthropic Computer Use that you can run on Mac computers to give Claude and other AI models autonomous access to your computer.. It is categorized as a Agent Tool with 846 GitHub stars.
mac_computer_use is primarily written in Python. It covers topics such as ai, anthropic, claude.
You can find installation instructions and usage details in the mac_computer_use GitHub repository at github.com/deedy/mac_computer_use. The project has 846 stars and 134 forks, indicating an active community.
The top alternatives to mac_computer_use on Agent Skills Hub include open-computer-use, open-computer-use, Unity-MCP. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.