Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Lets Claude drive your REAL mouse, keyboard and screen - works in your own logged-in apps.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"realhands": {
"command": "uvx",
"args": [
"realhands"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add realhands -- uvx realhands프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"realhands": {
"command": "uvx",
"args": [
"realhands"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"realhands": {
"type": "stdio",
"command": "uvx",
"args": [
"realhands"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 kanishka089 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.2)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Happo
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Review Happo's visual and accessibility diffs: inspect comparisons, accept or reject, report flakes.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
An MCP server that lets Claude operate your real computer the way a human does — moving the actual mouse, clicking, typing, and reading the actual screen.
Unlike OpenAI Operator, browser-use, or Playwright agents (which spin up a separate, isolated, logged-out Chrome), this drives the physical OS cursor and keyboard. So it works in your own Chrome with your own logged-in sessions — and in every other app — because it's just a human at the keyboard, as far as any website can tell.
Status: LIVE and battle-tested. Registered with Claude Code as the user-scope MCP `realhands` (tool mcp__realhands__computer) and ✓Connected since 2026-06-02. On 2026-06-09 it drove the user's real, logged-in Chrome through a complete Google Play Console deployment (app upload, release notes, submission) end-to-end.
The server is registered as
realhandsrather thancomputer-usebecause the name
"computer-use" is reserved in Claude Code.
Claude (Desktop or Code) is the agent loop. You type a task; Claude calls the single computer tool in a see → think → act cycle:
See —
screenshotreturns the real screen (downscaled to ~1280px for grounding accuracy)
→ Think — Claude picks the next action + pixel coordinates
→ Act — the server moves the real mouse / types on the real keyboard
→ a fresh screenshot comes back automatically after every action, and it repeats.
Two Windows-specific details make clicks land accurately (src/screen.py):
SetProcessDpiAwareness(2) is set at import time so screenshot pixels == pyautogui cursor coordinates even under display scaling (125% / 150% / …).COMPUTER_USE_MAX_DIM on the longest side before sending; incoming click coordinates are scaled back up to real pixels. The scale factor is a pure function of monitor geometry + MAX_DIM, so mapping never depends on which screenshot ran last. Coordinates are clamped inside the target monitor so a stray click can't fly off-screen. Each axis is rounded down to a whole 28px vision patch, so the two axes can scale very slightly differently (<2.2%); to_real() maps each with its own factor and stays exact.Multi-monitor: every call takes an optional monitor index (1 = primary, 2.. = others, 0 = the whole virtual desktop). action="monitors" enumerates the setup. Origins may be negative for screens left/above the primary — to_real() handles the offset. Use the same monitor for a click as for the screenshot you're clicking on.
src/realhands/
server.py FastMCP server "computer-use"; the single computer tool (action enum modeled on Anthropic's reference computer_20250124 tool); runs one action or a batch of steps, then returns status text + at most one screenshot screen.py DPI awareness, mss capture, patch-aligned downscale, model-space -> real-pixel mapping, unchanged-screen detection input.py pyautogui mouse/keyboard execution; xdotool-style key-name translation (Return, Page_Down, ctrl+a, super, ...); clipboard-paste fast path for long/Unicode/multiline typing (preserves your existing clipboard); activate_window via win32 AttachThreadInput safety.py kill switches + lazy arm / stand-down lifecycle config.py .env-driven configuration (all defaults are sensible; .env is optional) install.py one-shot installer: venv, deps, .env, Claude Desktop registration
Stack: Python 3.10/3.11 · mcp (FastMCP, stdio) · pyautogui · mss · pillow · pynput · keyboard · pyperclip · python-dotenv — plus pygetwindow and pywin32 for activate_window.
computer toolA single tool with an action parameter:
| Action | What it does |
|---|---|
screenshot | Capture the screen (always start a task with this) |
cursor_position | Report the real mouse position |
monitors | List detected monitors (for multi-screen setups) |
mouse_move | Glide the cursor to coordinate |
left_click / right_click / middle_click / double_click / triple_click | Click at coordinate (or current position) |
left_click_drag | Drag from text="x1,y1" to coordinate=[x2,y2] |
left_mouse_down / left_mouse_up | Press / release the left button |
scroll | Scroll at coordinate (scroll_direction + scroll_amount notches) |
type | Type text (clipboard-paste path for long/Unicode/multiline) |
key | Press a key or chord — "Return", "ctrl+s", "alt+Tab" |
hold_key | Hold keys for duration seconds |
activate_window | Bring an app to the front by title substring (beats Windows' foreground-lock; far more reliable than clicking the taskbar) |
wait | Sleep duration seconds, then screenshot |
stop | Stand down: close the STOP overlay + release the panic hotkey (call as the final action) |
Coordinates are in the pixel space of the most recent screenshot; its size is reported with every capture. After every non-screenshot action the tool waits ~0.4s for the UI to settle and returns a fresh screenshot.
Screenshots dominate the cost of driving a desktop, and not just once: every image stays in the conversation and is re-sent as history on each later turn. Claude bills vision in 28×28 patches — tokens = ⌈w/28⌉ × ⌈h/28⌉ — so this server does four things to keep the bill down.
Batch steps. Pass steps (a list of action dicts) instead of one call per action and the whole run shares one screenshot at the end:
{"steps": [{"action": "left_click", "coordinate": [420, 300]},
{"action": "type", "text": "hello@example.com"}, {"action": "key", "text": "Tab"}, {"action": "type", "text": "secret"}, {"action": "key", "text": "Return"}]}
That is 1 125 visual tokens instead of 5 625, and one round trip instead of five — the larger saving, since each avoided turn also avoids re-sending the entire transcript. A failing step stops the run, reports which step failed, and still returns the screen. Add "screenshot": false to skip the trailing image too.
Patch-aligned downscaling. A dimension that isn't a multiple of 28 pays for a partial patch row/column carrying almost no pixels. From a 1920×1080 primary the default 1260×700 is exactly 45×25 patches = 1 125 tokens, versus 1 196 for 1280×720 — 6% off for 1.5% fewer pixels.
Unchanged-screen suppression. If under CHANGE_THRESHOLD of pixels moved since the last image sent, the reply is a line of text instead of a screenshot. A real desktop never produces two byte-identical frames (clock, caret, hover states), so this is a threshold, not an equality check. After MAX_SKIPS suppressions in a row it force-sends one, so the model can't fly blind if it lost the earlier image to context compaction.
Right-sized images. COMPUTER_USE_MAX_DIM trades grounding accuracy against cost — from a 1920×1080 primary: 1792 → 2 304 tokens, 1260 → 1 125 (default), 1036 → 777, 896 → 576. Keep the long edge ≤ 2576 px: an image returned inside a tool_result is *rejected* rather than downscaled when it exceeds the model's limit.
COMPUTER_USE_IMAGE_FORMATis not a token lever — Claude bills by pixel
dimensions, so a JPEG and a PNG of the same screenshot cost exactly the same. JPEG
only cuts payload bytes (~977 KB → ~141 KB here), which helps latency at some risk
to small-text legibility.
This is fully autonomous: it does not ask before each action. Three independent kill switches (src/safety.py):
FailSafeException and the action aborts instantly.os._exit(1)).Lazy arm / stand-down: the overlay and the global panic hotkey are armed lazily on the first action of a task, not at server startup — idle sessions show nothing and grab no hotkeys. They stand down when the agent calls action="stop" at the end of a task, and re-arm automatically on the next action. (The STOP overlay is a single persistent window that is *hidden* when dormant, never destroyed — recreating it was a crash hazard.) An optional idle auto-stand-down is available via COMPUTER_USE_IDLE_STOP but is disabled by default: an agent's thinking time between tool calls easily exceeds any short idle window, so a non-zero value would stand the agent down mid-task.
Pacing also helps you stay in control: every action is followed by a configurable pause (COMPUTER_USE_PAUSE) and the cursor glides rather than teleports (COMPUTER_USE_MOVE_DURATION), so you can watch and interrupt.
Don't leave it unsupervised on anything that can spend money, send messages, or delete data.
Requires Python 3.10 or 3.11 (3.13+ untested; avoid the 3.14 beta).
uvx (always the latest version)Nothing to install up front, and you get every release automatically — uvx resolves the newest published version each time the server starts, so a restart of your MCP client is the whole upgrade process. Requires uv.
uvx realhands@latest
Drop the @latest (uvx realhands) if you would rather let uv reuse whatever version it already has cached.
pip install realhands
This installs the realhands console script and the importable realhands package. Run the server with either realhands or python -m realhands.server.
Pick this over uvx when you want a pinned version that never changes underneath you, or when the machine may be offline at startup — uvx realhands@latest needs to reach PyPI each time it launches. The trade-off is that upgrades become manual:
pip install --upgrade realhands
Then restart your MCP client — clients bind their servers at session start, so a running session keeps the old code until it restarts.
git clone https://github.com/kanishka089/computer-use-mcp
cd computer-use-mcp py -3.10 install.py
This creates .venv/, installs the package + deps (editable), copies .env.example to .env if missing, and registers the server in Claude Desktop's config (backing up any existing config). Restart Claude Desktop, then look for the computer-use tool.
Register it as a user-scope stdio server named realhands. This form auto-upgrades — each new session resolves the latest release, so you never have to think about it:
claude mcp add realhands --scope user -- uvx realhands@latest
The tool then appears as mcp__realhands__computer in every project.
If you installed with pip instead and want a pinned version, point it at the Python that has the package (and run pip install --upgrade realhands yourself to move up):
claude mcp add realhands --scope user -- python -m realhands.server
Already registered on an older version? Re-point it at the auto-upgrading form:
`powershell
claude mcp remove realhands --scope user
claude mcp add realhands --scope user -- uvx realhands@latest
`
Removing and re-adding an MCP mid-session drops this session's connection to it — the
new registration is picked up on the next Claude Code start.
On 0.1.x? Upgrade.
mcp2.0 removed the API 0.1.x imports, so while an install
made back
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요