Indexes the coding-agent sessions already sitting on your disk — months of history from before you installed it — and serves them back over MCP. 3.5 GB searched in ~1.5 ms, no LLM, no embeddings.
nuphus-mcp
Summary
Computer use for any MCP client: 36 tools covering screenshots, window control, mouse and keyboard, and Chrome over CDP, with local OCR built in and vision on your own key.
Features
- 36 MCP tools — 15 desktop, 21 browser
- Screenshots, window activate/move/resize, mouse, keyboard, clipboard
- Chrome automation over the DevTools Protocol
- Local OCR with PaddleOCR plus optional YOLO icon detection — no key needed
- Vision through your own OpenAI-compatible or Anthropic-native model (BYOK)
- Single Rust binary over stdio — no daemon, no network service
- --confirm-write gating and a documented threat model with per-tool safety annotations
Installation
Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.
Description
nuphus-mcp is a cross-platform desktop-automation server that gives any MCP client the ability to see and drive the machine it runs on. It speaks JSON-RPC 2.0 over stdio — one binary, no daemon, no network service — so Claude Desktop, Cursor, VS Code, Copilot or any other client can connect and immediately control the screen, windows, keyboard, mouse and Chrome.
The 36 tools
15 desktop tools: screen size, screenshot as PNG or base64, window listing, per-window activate / screenshot / move / resize / info, mouse click, drag, scroll and position, keyboard input and hotkeys, clipboard write and clear. These are implemented on the desktop-api crate over xcap and Win32, with no Tauri dependency.
21 browser tools driving Chrome through the DevTools Protocol via the nuphus-browser crate.
Seeing the screen
Two complementary tools handle perception. desktop_perceive runs local OCR with PaddleOCR — models download on first run, with optional YOLO icon detection — so text on screen is readable without sending anything anywhere. desktop_vision sends a screenshot to your own vision model over an OpenAI-compatible or Anthropic-native API. Used together they give an agent both semantic understanding and precise coordinates.
Desktop and browser automation need no API key at all; only the vision tool does, and it is bring-your-own.
Safety
Write operations can be gated behind --confirm-write, or the equivalent environment variable so one setting covers every MCP client on the machine. The repository documents a threat model and per-tool safety annotations — worth reading before you hand an agent your mouse.
Written in Rust, MIT licensed, and mirrored on Gitee with Chinese documentation for access from mainland China.
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