Vision Bridge

One vision layer for AI agents on Windows — a single MCP server that lets any agent see and act on the screen: native desktop apps, Electron/Chromium windows, and the browser — undetected.

Most agent setups end up with a pile of disconnected tools: one for the browser, one for native windows, one for OCR, each with its own quirks. vision-bridge hides all of that behind four verbs — capture, act, find, wait_for — so the agent asks "what's on screen?" and "click this" the same way everywhere. The router picks the right backend underneath.

It is designed for text-only brains too (e.g. DeepSeek, local LLMs): the screen is returned as structured text, not pixels, so an agent that can't consume images can still understand and drive the UI.

• 🖥️ Desktop — native Win32/WPF/UWP via UI Automation (fast, exact, coordinate-free clicks).
• 🧩 Electron/Chromium — OCR fallback when the a11y tree is blind.
• 🌐 Browser, undetected — drive your real Chrome over CDP (live cookies, sessions never drop) or a stealth browser (patchright, persistent profile, navigator.webdriver = false).
• 🔌 Standard MCP — stdio transport, works with Claude Desktop, Cline, Cursor, or any custom agent, no code changes.

Deep-dive design & rationale (RU): docs/01_architecture.md

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Why (for humans)

An agent that "sees the screen" usually means gluing Playwright + some UIA library

• Tesseract together and teaching the model three different mental models. This project makes that one contract. Add a backend, keep the same four tools. The agent never learns "how" — only "what".

Why (for agents)

If you are an LLM agent reading this to use the server: call capture(target) to get a list of Elements (each with a stable id) plus a flat text dump of the screen. Then call act(element_id, action, ...). You never compute coordinates or CSS selectors — you address elements by the id from the last capture/find. id prefixes tell you the backend (u=desktop, o=OCR, b=browser); the server routes automatically.

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Tools

Tool	Purpose
capture(target, mode="auto")	Screen of a target → {ok, elements[], text, method_used}
act(element_id, action, text="", value="")	click / double_click / type / set_value / focus / read / scroll
find(query, target="", mode="auto")	Locate one element by name/value
wait_for(query, target="", timeout_s=10, mode="auto")	Poll until an element appears
browser_open(mode, url, cdp_url, user_data_dir, channel, headless)	Connect/launch a browser
browser_goto(url)	Navigate the open browser
browser_close()	Close the browser session

target: a window title substring for desktop, or "browser" for the page. Empty target = foreground window. mode: auto | uia | ocr | browser.

Element

{
  "id": "u17",                 // stable ref; prefix = backend (u/o/b)
  "role": "button",            // button | textbox | link | text | ...
  "name": "OK",
  "value": null,
  "bbox": [120, 80, 60, 24],   // screen coords [x, y, w, h]
  "state": { "enabled": true, "focused": false, "visible": true, "checked": null },
  "backend": "uia"
}

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Install

uv sync                      # core: MCP + pydantic
uv sync --extra desktop      # UIA + OCR (uiautomation, pytesseract, mss)
uv sync --extra browser      # stealth/CDP browser (patchright)

OCR needs the Tesseract-OCR binary (not the pip package): install it (e.g. winget install UB-Mannheim.TesseractOCR). For extra languages, pull the models into a local tessdata/ folder (no admin rights needed — picked up automatically):

uv run python scripts/download_langs.py            # Russian + English (default)
uv run python scripts/download_langs.py deu fra     # any Tesseract languages

Russian is supported out of the box via the script above (rus+eng). The backend finds tessdata/ next to the project or via VISION_BRIDGE_TESSDATA.

Run

uv run vision-bridge                          # stdio server
uv run mcp dev src/vision_bridge/server.py    # MCP Inspector

Connect to an agent

Any MCP client with a command/args config:

{
  "servers": {
    "vision-bridge": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/vision-bridge", "vision-bridge"]
    }
  }
}

Examples

Desktop:

capture("Notepad")                      # → elements + text of the window
act("u0", "type", text="hello world")   # type into the document
act("u0", "read")                       # → { content: "hello world" }

Browser, undetected — real Chrome (max stealth, keeps your sessions):

# start Chrome with a debug port and your profile first:
chrome.exe --remote-debugging-port=9222 --user-data-dir="C:\path\profile"

browser_open(mode="cdp", cdp_url="http://localhost:9222")
capture("browser")
act("b3", "type", text="search query")

Browser — standalone stealth profile:

browser_open(mode="stealth", url="https://example.com",
             user_data_dir="C:\\path\\profile")   # navigator.webdriver = false

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How routing works

              capture(target, mode="auto")
                        │
   target=="browser" ───┼─── desktop window ───────────────┐
        │               │                                  │
   ┌────▼────┐    UI Automation a11y tree            (few elements? →)
   │ browser │    ┌──────────────┐                   ┌──────────────┐
   │ cdp /   │    │     UIA       │  ── fallback ──▶  │  OCR (Tess.) │
   │ stealth │    └──────────────┘                   └──────────────┘
   └─────────┘

Status & limits

Stages 0–3 implemented and tested live on real apps (Notepad, Chrome). Roadmap: agent skill + scenario tests, optional OmniParser for clickable boxes instead of plain OCR text.

• Stealth is not 100% undetectable (Cloudflare/DataDome evolve) — prefer mode="cdp" against real Chrome for maximum stealth and session persistence.
• Console output with non-ASCII: run under PYTHONUTF8=1 (does not affect the UTF-8 MCP protocol).

License

MIT — see LICENSE.

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Кратко (RU)

Единый слой зрения для AI-агентов на Windows как один MCP-сервер. Четыре глагола — capture, act, find, wait_for — работают одинаково для нативных окон, Electron/Chromium (через OCR) и браузера. Экран отдаётся текстом, поэтому подходит даже текстовым моделям (DeepSeek и др.). Браузер — незаметно: реальный Chrome по CDP (живые куки, сессии не рвутся) или стелс-браузер на patchright (navigator.webdriver=false). OCR понимает русский (uv run python scripts/download_langs.py). Архитектура и план — в docs/01_architecture.md.