Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@windows-computer-use-mcp Open Notepad, type 'Hello, world!', and save the file."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A tool for agents, and an agent itself.
You | It |
Use it as an MCP server | Claude, Cursor, DeepSeek call |
Use it as an autonomous agent | Give it a goal: |
Use it as a webapp |
|
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.
Method | Command / Config |
MCP stdio (Cursor, Claude Desktop) |
|
HTTP streamable (any MCP HTTP client) |
|
Web operator UI |
|
Desktop app (NSIS installer) | Download from Releases — zero deps |
See INSTALL.md for detailed setup. Run just demo for examples.
Related MCP server: EZComputerCtrl MCP
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
Doc | Content |
Setup: desktop app, uv, MCP config | |
Full documentation hub | |
Python dependency deep dive | |
Browser automation with Playwright MCP | |
OCR system — Tesseract setup, limitations, competition | |
Dogfooding: using the tool to test its own NSIS installer | |
Improvement roadmap short/medium/long term | |
HITL, kill switch, opt-in features | |
Portmanteau tool reference | |
Test suite guide and e2e setup | |
Runnable demos | |
MCPB bundle packaging | |
Operator UI build/dev guide | |
Release history |
Port | Service |
10788 | Frontend — Vite operator UI |
10789 | Backend — FastAPI + FastMCP HTTP |
stdio | MCP transport (port-free) |
Repo | What it does |
Raw input recording/replay via AHK | |
Playwright browser control — for webapps, HTML DOM, websites | |
Sandbox / VM isolation | |
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.
MIT — Copyright (c) 2026 Sandra Schipal.
This server cannot be deployed
MCP server for building and testing AI agents with multi-model experimentation and insights.
MCP Server for an Agent Task Marketplace
Unified MCP Server is a remote MCP connector for AI agents and vertical AI products that provides access to 22,000+ authorized SaaS tools across 400+ integrations and 24 categories directly inside LLMs (Claude, GPT, Gemini, Cohere). Tools operate only on explicitly authorized customer connections, enabling agents to safely read and write against live third-party systems.
