High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
MCP server for Windows desktop automation
This repo connects an agent to Windows through MCP tools for clicking, typing, screenshots, OCR, and UI inspection. It can also run as an autonomous mission engine that plans, retries, verifies, and reports on desktop tasks.
Builders who want an agent to operate Windows apps, inspect screens, and carry out multi-step desktop work.
You can have an agent control Windows software directly instead of asking you to click through every step.
What it does
Desktop control tools
Exposes 22 MCP tools for mouse, keyboard, screenshot, OCR, and UI inspection.
Autonomous missions
Runs goal-based jobs that plan actions, retry failures, and verify the result.
Web operator UI
Provides a browser dashboard with human-in-the-loop controls, logging, and crawler views.
Desktop app packaging
Bundles the system into a Windows app through Tauri and NSIS.
Telemetry and replay
Logs actions to SQLite and supports macro recording and replay for repeatable workflows.
Adaptive element discovery
Finds UI targets using title, IDs, class names, and OCR fallbacks.
README
windows-computer-use-mcp
A tool for agents, and an agent itself.
| You | It |
|---|---|
| Use it as an MCP server | Claude, Cursor, DeepSeek call automation_click, automation_screenshot, automation_ocr — 22 tools |
| Use it as an autonomous agent | Give it a goal: automation_mission(run="install app, verify UI, screenshot result") — it plans, executes, retries, and reports |
| Use it as a webapp | start.ps1 opens a React dashboard at http://127.0.0.1:10788 with HITL, crawler, logging |
| Use it as a desktop app | The NSIS installer bundles everything into one binary — no Python, no uv, no git needed |
Exhibit A: 100 Tauri/NSIS installers, one unattended run, $2 in LLM costs. Install, screenshot, verify, report — zero human intervention. That is what agentic Windows automation looks like at scale.
Built on pywinauto. Read docs/SAFETY.md before production use.
Quick Start
| Method | Command / Config |
|---|---|
| MCP stdio (Cursor, Claude Desktop) | { "mcpServers": { "windows-computer-use": { "command": "uv", "args": ["--directory", "<PATH>", "run", "windows-computer-use-mcp"] } } } |
| HTTP streamable (any MCP HTTP client) | { "mcpServers": { "windows-computer-use": { "url": "http://127.0.0.1:10789/mcp" } } } |
| Web operator UI | .\start.ps1 → http://127.0.0.1:10788 |
| Desktop app (NSIS installer) | Download from Releases — zero deps |
See INSTALL.md for detailed setup. Run just demo for examples.
Features
- Window Management — find, activate, maximize, minimize, position, close
- Mouse & Keyboard — click, drag, type, hotkeys, app shortcuts
- UI Elements — inspect, click, read text, verify state via UIA / Win32
- Visual Intelligence — screenshots, OCR, template matching
- Autonomous Missions — give it a goal, it plans and executes with retry + verification
- Macro Recording — record any UI sequence, replay, verify outcomes
- Multi-App Workflows — chain actions across Notepad, Calc, Paint, or any Windows app
- Telemetry — every action logged to SQLite; query failure patterns by tool
- Adaptive Location — auto-cascades through title/auto_id/control_id/class/OCR to find elements
- Face Recognition — optional, off by default
Documentation
| Doc | Content |
|---|---|
| INSTALL.md | Setup: desktop app, uv, MCP config |
| docs/README.md | Full documentation hub |
| docs/py-stack.md | Python dependency deep dive |
| docs/composing-with-playwright.md | Browser automation with Playwright MCP |
| docs/ocr.md | OCR system — Tesseract setup, limitations, competition |
| docs/cua-nsis-certification.md | Dogfooding: using the tool to test its own NSIS installer |
| docs/ROADMAP.md | Improvement roadmap short/medium/long term |
| docs/SAFETY.md | HITL, kill switch, opt-in features |
| docs/TOOLS.md | Portmanteau tool reference |
| tests/README.md | Test suite guide and e2e setup |
| examples/README.md | Runnable demos |
| mcpb/README.md | MCPB bundle packaging |
| web_sota/README.md | Operator UI build/dev guide |
| CHANGELOG.md | Release history |
Ports
| Port | Service |
|---|---|
| 10788 | Frontend — Vite operator UI |
| 10789 | Backend — FastAPI + FastMCP HTTP |
| stdio | MCP transport (port-free) |
Related
| Repo | What it does |
|---|---|
| autohotkey-mcp | Raw input recording/replay via AHK |
| browser-mcp | Playwright browser control — for webapps, HTML DOM, websites |
| virtualization-mcp | Sandbox / VM isolation |
| windows-operations-mcp | Registry, services, accounts |
Browser vs desktop: This server drives Win32 / UI Automation. For HTML/DOM and websites, pair with browser-mcp (Playwright). Both MCPs can run side by side — use one profile that loads both and let the LLM pick the right tool for the target.
Fleet standards: mcp-central-docs.
License
MIT — Copyright (c) 2026 Sandra Schipal.
Files in the repo
- .github
- .snapshots
- .windsurf
- cua-reports
- docs
- examples
- hooks
- mcpb
- native
- ocr_scans
- presets
- scratch
- scripts
- skills
- src
- tests
- web_sota
- .cursorignore
- .cursorrules
- .env.example
- .gitattributes
- .gitignore
- .mcpbignore
- .pre-commit-config.yaml
- AGENT_PROTOCOLS.md
- AGENTS.md
- BUILD_LOG.md
- CHANGELOG.md
- CLAUDE.md
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- fleet-start.config.ps1
- glama.json
- INSTALL.md
- justfile
- justfile.bak-20260729_133948
- justfile.bak-20260729_134055
- LICENSE
- llms-full.txt
- llms.txt
- MANIFEST.in
- manifest.json
- mcpb.json
- paint_elements.json
- pyproject.toml
- pytest.ini
- README.md
- renovate.json
- run_server.py
- screenshot_demo.png
- SECURITY.md
- setup.py
- start.bat
- start.ps1
- uv.lock
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