About Computer Use AI SDK
Computer Use AI SDK is an open source desktop control SDK from screenpipe, built around an MCP server and matching clients. It runs natively on macOS and works with desktop-rendered elements rather than pixel recognition. It suits developers who want to build agents that automate desktop tasks.
Key features
- 01Runs natively on macOS without a virtual machine
- 02Operates on desktop-rendered elements instead of pixels
- 03Provides tools to launch apps, read content, click and press keys
- 04Includes a CLI client and a Next.js web client
- 05Ships a Hello World template for custom agents
Use cases
- 01Letting an AI perform actions in desktop apps
- 02Building custom agent workflows that run on a schedule
- 03Combining with other MCP servers, such as filling a spreadsheet from chat history
MCP support
The project includes an MCP server that exposes desktop control tools such as launching apps, reading content, clicking and pressing keys, along with a matching MCP client example.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEComputer Use AI SDK
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We've built an MCP server that controls computer
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You've heard of OpenAI's operator, you've heard of Claude's computer use. Now the open source alternative: Computer Use SDK from screenpipe.
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It's native on macOS—no virtual machine bs, no guardrails. Use it with any app or website however you want.
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No pixel-based bs—it relies on underlying desktop-rendered elements, making it much faster and far more reliable than pixel-based vision models.
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You can now build your own agents getting started with our simple Hello World Template using our MCP server and client.
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There are tools that our MCP Server provides out of the box:
- Launch apps
- Read content
- Click
- Enter text
- Press keys
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These will be computational primitives to allow the AI to control your computer and do your tasks for you. What will you build? Come check us out at https://screenpi.pe
Demos
agent sending a message
https://github.com/user-attachments/assets/f8687500-9a8c-4a96-81b6-77562feff093
get latest whatsapp messages
open arc browser
Get started
git clone https://github.com/m13v/computer-use-ai-sdk.git
cd MCP-server-client-computer-use-ai-sdk
# Install Rust (if not already installed)
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# Install Node.js and npm (if not already installed)
# Visit https://nodejs.org/ or use nvm
# run backend server
cd mcp-server-os-level
cargo run --bin server
# keep it running
Option 1: CLI Interface
# run CLI interface client in a new terminal (good for debugging)
cd mcp-client-cli-interface
npm install # install dependencies first
# Set your Anthropic API key as an environment variable
export ANTHROPIC_API_KEY=sk-ant-xxxx # Replace with your actual Anthropic API key
# For Windows, use: set ANTHROPIC_API_KEY=sk-ant-xxxx
# For permanent setup, add to your shell profile (.bashrc, .zshrc, etc.)
npx tsx main.ts
Option 2: Web app Interface
# run CLI interface client in a new terminal (good for debugging)
cd mcp-client-nextjs
npm install # install dependencies first
# Set API key via command line
echo "ANTHROPIC_API_KEY=sk-ant-XXXXXXXX" > .env # replace XXXXXXXX with your actual key
# Or append if you want to keep other env variables
# echo "ANTHROPIC_API_KEY=sk-ant-XXXXXXXX" >> .env
npm run dev
# go to provided localhost web page
What do I do with it?
- Build custom worfklows of agents to performs various actions
- Build custom UI to make it easy for users to automate their computer work
- Save workflow and run in cron
- Combine with other MCP servers to do something cool, e.g.: fill out a google sheet based on the history of people i talk to throughout the day
Request features and endpoints in github issues
https://github.com/m13v/computer-use-ai-sdk/issues/new/choose
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.