mouse-mcp
Enables AI agents to interact directly with Windows environments via hardware-level HID control.
Hardware mouse MCP server for AI agents on Windows x64. USB HID control and voice dictation; requires compatible uMouse hardware and firmware. 面向 AI 智能体的硬件鼠标 MCP:USB HID 控制与语音听写,需要兼容的 uMouse 设备与固件。
- Ask Claude to move the mouse cursor to specific screen coordinates
- Automate mouse clicks and hardware inputs via USB HID control
- Use voice dictation to input text through the hardware mouse
Enables AI agents to interact directly with Windows environments via hardware-level HID control. This bridges the gap between LLM reasoning and physical interface execution, allowing for automated testing and GUI-based task completion.
Automation engineers and AI researchers developing agents that require reliable, low-level hardware interaction on Windows systems.
https://github.com/SonicloudTech/mouse-mcp
By SonicloudTech
How to Get It
claude mcp add mouse-mcp -- npx -y mouse-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Move the mouse cursor to specific screen coordinates
Trust Signals Auto-scanned
Data & Access
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 64 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 64 GitHub stars; contributors unknown; last commit 0d ago; license MIT.