Cua Driver Serves Its Desktop-Automation Skill Over MCP
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- x.com
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1/ Your agents can now load Cua Driver skills through Skills over MCP. Available in v0.28.0+, alongside modern MCP support. Give compatible agents desktop tools and guidance through one stdio connection. Get started: https://t.co/J1frbEbZTQ

2/ Discover the skill, read its instructions, then use the desktop tools. The bundled skill is matched to your Driver release. MCP resource clients can read it at: skill://cua-driver/SKILL.md Your client decides when to activate it.

3/ The skill teaches your agent how to choose tools, target windows and elements, preserve focus, and verify each action. It includes guidance for macOS, Windows, and Linux, plus browser, recording, and embedding workflows.

4/ Available in Cua Driver 0.28.0+ through cua-driver mcp. Client setup: https://t.co/Sw3ANcuqR9

Context
Cua says agents can now load Cua Driver skills through Skills over MCP, available in Cua Driver v0.28.0 and later. A is instructions that teach an how to use tools, rather than the tools themselves. Cua says the bundled skill covers how to choose tools, target windows and elements, preserve focus and verify each action, with guidance for macOS, Windows and Linux plus browser, recording and workflows.
Through cua-driver , a compatible agent gets the desktop tools and that guidance over one stdio connection. MCP resource clients can read the skill at skill://cua-driver/SKILL.md, the bundled skill is matched to the installed Driver release, and the client decides when to activate it.
- MCP — The Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.
- agent skill — A reusable instruction file that teaches an agent how to do one job well — the procedure, the tools, and what counts as done.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
- embedding — A list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.
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