Universal Computer Control MCP

Give your AI agent eyes and hands on any computer. Observe → understand → act → verify. No browser MCPs. No Playwright. Just real control.

A cross-platform computer control MCP server that lets an AI agent operate a Windows or Linux computer like a human: observe the screen → understand the UI → choose an action → perform it → observe again → verify → recover if needed.

The system deliberately has no dependency on Chrome MCP, browser MCP, Playwright MCP or any other external MCP server. Browsers, IDEs, office suites, terminals, file managers, Electron apps and canvas-heavy applications are all just GUI applications. Multiple backends live inside the server and the best available mechanism is chosen automatically per action.

                AI Agent / LLM
                       | MCP (stdio)
                       v
        +------------------------------+
        | Universal Computer MCP Server |
        +---------------+--------------+
                        v
        +------------------------------+
        |   Computer Control Engine    |  <- usable WITHOUT MCP
        +---------------+--------------+
            |            |             |
            v            v             v
     Accessibility   Vision/OCR    Physical Input
       Layer            Layer          Layer
      |      |         |      |       |       |
     UIA   AT-SPI     OCR  OpenCV   Mouse  Keyboard
    (Windows)(Linux) Tesseract  VLM  PyAutoGUI  OS APIs

Highlights

• 29 stable MCP tools under the computer. namespace — capabilities, not implementation details. No pyautogui_click, no ocr_click, no playwright_click.

• Interaction hierarchy per action: Windows UIA → Linux AT-SPI → semantic element → OCR text → image template → vision-language model → coordinates → PyAutoGUI. Every fallback is automatic.

• computer.observe is the core tool: one structured snapshot with screen geometry, active window, cursor, OCR'd text and normalized UI elements (stable element_N ids within a cycle).

Related MCP server: planchette

Requirements

Installation

Windows 10/11

git clone https://github.com/adkdev200/universal-computer-control.git && cd universal-computer-control
powershell -ExecutionPolicy Bypass -File scripts\install_windows.ps1

Manual steps:

1. Install Python 3.11+ (winget install -e --id Python.Python.3.12), tick Add to PATH.

2. python -m venv .venv && .venv\Scripts\pip install -e ".[input,windows,ocr,vision,screenshot,vlm]"

3. Install Tesseract OCR: winget install -e --id UB-Mannheim.TesseractOCR (set ocr.tesseract_cmd in config.yaml if it is not on PATH).

4. Run: .venv\Scripts\universal-computer-control (alias: .venv\Scripts\ucc)

Windows UI Automation needs no extra permissions. If you run the server elevated, non-elevated windows may refuse automation (UIA integrity levels).

Linux (X11 or XWayland)

git clone https://github.com/adkdev200/universal-computer-control.git && cd universal-computer-control
bash scripts/install_linux.sh --yes     # add --no-sudo to skip system packages
./.venv/bin/ucc-doctor                  # verify every backend, exact fix hints

The installer is fully non-interactive with --yes: it installs system packages (wmctrl/xdotool/xclip/scrot/tesseract/at-spi2-core), all Python extras, and a ready ~/.universal-computer/config/config.yaml with OCR, template matching and the VLM provider enabled. ucc-doctor then probes every backend live and prints copy-paste fix commands for anything missing. Note: even on machines with no wmctrl/xdotool/xclip installed, the Linux window backend now works through a built-in python-Xlib (EWMH/ICCCM) fallback - the system tools only make it more robust.

Manual steps:

1. Python 3.11+ and system packages:

   sudo apt install python3 python3-venv python3-pip \
                    wmctrl xdotool xclip scrot \
                    tesseract-ocr at-spi2-core

2. python3 -m venv .venv && ./.venv/bin/pip install -e ".[input,linux,ocr,vision,screenshot,vlm]"

3. Run from a graphical session: ./.venv/bin/universal-computer-control (alias: ./.venv/bin/ucc)

AT-SPI requirements (accessibility): at-spi2-core must be running (it is on desktop distros) and for GNOME/GTK apps enable gsettings set org.gnome.desktop.interface toolkit-accessibility true.

X11 vs Wayland: X11 is fully supported. On Wayland-with-XWayland, input and screenshots work through XWayland but foreign window management may be restricted by the compositor. On pure Wayland (no DISPLAY), the window backend disables itself with a warning; AT-SPI still works for cooperating toolkits. See docs/TROUBLESHOOTING.md.

Registering the server with an MCP client

claude_desktop_config.json (see examples/mcp-config.example*.json):

{
  "mcpServers": {
    "universal-computer": {
      "command": "/absolute/path/to/universal-computer-control/.venv/bin/python",
      "args": ["-m", "universal_computer"],
      "env": {}
    }
  }
}

Any MCP client that speaks stdio works the same way. The engine is also a plain library — no MCP required:

from universal_computer import ComputerControlEngine, load_config

computer = ComputerControlEngine(load_config())
obs = await computer.observe("normal")
await computer.click("Continue")
await computer.type("hello")

Tools (MCP API)

computer.observe returns a normalized snapshot:

{
  "ok": true,
  "id": "obs_17",
  "level": "normal",
  "screen": {"width": 1920, "height": 1080, "monitors": [...]},
  "active_window": {"title": "Google Chrome", "application": "chrome.exe", "process_id": 1234},
  "cursor": {"x": 812, "y": 530},
  "elements": [
    {"id": "element_1", "role": "button", "name": "Continue",
     "bbox": [1050, 700, 1170, 750], "source": "uia", "confidence": 0.99}
  ],
  "ocr": [
    {"text": "Continue", "bbox": [1050, 700, 1170, 750], "confidence": 0.97}
  ]
}

computer.backend_status reports per-backend health:

{
  "pyautogui": {"available": true, "healthy": true},
  "uia":       {"available": true, "healthy": true},
  "atspi":     {"available": false, "healthy": false,
                "error": "pyatspi import failed (...); install python3-pyatspi"},
  "ocr":       {"available": true, "healthy": true}
}

Configuration

config.yaml (see config.example.yaml) plus UCC_ environment overrides with __ nesting:

UCC_ENGINE__VERIFICATION_MODE=strict
UCC_SECURITY__MODE=standard
UCC_SECURITY__ALLOWED_COMMANDS='["ls", "git status", "xdotool"]'
UCC_LOGGING__LEVEL=DEBUG
UCC_VISION__VLM__ENABLED=true

Configurable: observation level & caching, verification mode (off/basic/strict), PyAutoGUI pauses/failsafe, OCR provider & language, vision threshold, template directory, VLM endpoint (key read from the environment variable named in vision.vlm.api_key_env), security mode, allowlists, rate limits, timeouts, persistence retention, log levels and per-backend priorities (backends.priorities: {pyautogui: 5}).

Security model

Unquoted shell operators (;, |, &, `, <, >, $) only pass the allowlist when an entry matches the full command string — a bare program-name entry (git, python, ...) is not enough.

Always on: rate limiting (max_actions_per_minute), command timeouts, credential redaction in logs and command output, no clipboard/typed-text logging, close_window/run_command/launch_application confirmation gates, and the emergency stop — computer.emergency_stop() halts every subsequent action (checked before each attempt) and is persisted as a stop file so it survives restarts and can be triggered externally.

Extending

• New OCR: implement universal_computer.vision.base.OCRProvider (detect_text(image) -> list[OCRResult]) and register it in VisionServices.from_config.

• New vision model: implement VisionLanguageModel.locate_element (async, description → VisionResult with bbox). The OpenAI-compatible implementation shows the JSON contract.

• New platform (macOS): subclass the backends.base ABCs (InputBackend, ScreenshotBackend, AccessibilityBackend, WindowManagementBackend, ClipboardBackend, ApplicationBackend) and register them in core/bootstrap.py. Nothing else changes — the engine only knows capabilities.

• Template images: put PNGs in vision.template_dir; refer to them by name from computer.find_visual or as click targets.

Development

pip install -e ".[dev]"
pytest tests            # 160 unit + integration tests, no display needed
ruff check src tests

scripts/e2e_live_test.py is an end-to-end harness that boots its own Xvfb + openbox session, creates real X11 windows, and exercises every backend live (screenshots, OCR, window ops via both the tool paths and the python-Xlib fallback, OpenCV template matching, the VLM pipeline against a mock OpenAI-compatible endpoint, clipboard, input, launch, emergency stop):

python scripts/e2e_live_test.py             # full stack
python scripts/e2e_live_test.py --no-tools  # zero X11 tools: Xlib fallback

Unit tests run on any machine (OS-specific pieces are mocked). The integration test boots the real server over stdio. See docs/ARCHITECTURE.md for the module map and docs/TROUBLESHOOTING.md for platform-specific fixes.

Contributors & Acknowledgments

• Z.ai (GLM) — co-developer: MCP server, cross-platform backends, vision pipeline, python-Xlib window fallback and ucc-doctor diagnostics

• Claude Code (Anthropic) — co-developer: code generation, testing and plug-and-play hardening

• @adkdev200 — creator & maintainer

This project is built collaboratively with AI pair-programming: the majority of the codebase was written and reviewed by Z.ai's GLM and Anthropic's Claude Code under the direction of the maintainer.