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guarded-computer-use-mcp

by be1st6666

guarded-computer-use-mcp

CI Release License: MIT Node Platform Tests

Give your agent hands — without giving away the keys.

A Windows computer-use MCP server where every risky action stops and waits for a real human — a physical keystroke or click, which injected input, posted window messages and UIAutomation invocations cannot fake. 26 tools: screenshot, mouse, keyboard, UI Automation, OCR, windows, clipboard.

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TL;DR

Windows 10/11 · Node ≥ 18 · one runtime dependency (the official MCP SDK).

git clone https://github.com/be1st6666/guarded-computer-use-mcp
cd guarded-computer-use-mcp && npm install
npm run verify        # lint, 73 unit tests, policy samples, smoke test, audit chain
{ "mcpServers": { "computer": {
  "command": "node",
  "args": ["D:/path/to/guarded-computer-use-mcp/server.js"] } } }

Clicking Send, closing a window or pressing alt+f4 pops a dialog that only a physical key or click can answer; password managers, banking pages and shells are refused outright, and every action lands in a hash-chained audit.jsonl. It is still not a sandbox — read SECURITY.md before pointing it at anything that matters, and Install for the full setup.


WARNING

This server moves your real mouse and keyboard, with your user's privileges, on your real desktop. There is no sandbox and no undo.

It can send messages as you, delete files, and read everything on your screen — and what it reads is transmitted to your model provider.

The approval gate and the policy lists reduce the blast radius. They do not eliminate it. Read Risks and disclaimer before you point an agent at this.


Why

Most computer-use tools hand the model a keyboard and hope for the best. That is fine until the model mis-clicks into a chat window, an email, or a payment page — and there is no undo.

This one puts a gate in front of the dangerous part:

Approval dialog

The MCP server blocks on that dialog and uses its exit code. Three independent things stop the model from answering its own prompt:

  1. The gate lock — while a dialog is open, every input-injecting tool is refused (refused_by_approval_gate), and the check runs again after every await (including inside batch, whose step loop could otherwise resume after a parallel call opened a dialog). MCP handlers are async, so without this a parallel tool call (key("alt+a"), click(x, y) on Allow) would answer the dialog. That was a real bypass; it is fixed and covered by npm run test:inject and npm run test:lock.

  2. Only one dialog at a time — a second approval-requiring call is refused rather than stacking a dialog, so the lock cannot lift while another prompt is still unanswered.

  3. The dialog wants a physical event — it installs low-level keyboard and mouse hooks, discards every event carrying the Windows injected flag, and only accepts an allow from those hooks (a real Alt+A, or a real click inside Allow). SendInput from any automation tool, a posted BM_CLICK / WM_KEYDOWN, and a UIAutomation InvokePattern all fail this test, and the dialog says how many injected events it threw away.

{ "refused_by_approval_gate": true,
  "reason": "an approval dialog is waiting for a human decision — input-injecting tools are refused until it is answered" }

Built so a stray keystroke cannot approve anything:

Key

Effect

Enter

nothing — deliberately unbound

Esc / window close

deny

Alt+A / click Allow

allow (physical input only)

no answer in time

auto-deny (countdown shown)

The dialog also shows the actual arguments being executed (automationId=…, name=…), follows your OS language (Chinese/English), beeps, and stays on top. Tick remember this target for this session to stop being asked about the same tool + target until the server restarts.

Exit codes: 0 allow once · 1 deny · 2 timeout · 3 dialog unavailable (falls back to pending_safety_check) · 4 allow + remember for this session.

Flip it off any time when you don't want to be interrupted:

double-click  guard-panel.cmd      # the panel: four independent switches
double-click  toggle-approval.cmd  # quick toggle for the dialog only

Switches are HMAC-signed markers, and the server reads them on every call — changes apply instantly, no restart:

Switch

Marker file

Off means

Approval dialog

.approval-off

risky actions return pending_safety_check instead of asking you

Deny lists

.guard-off

the deny lists, the allow list and the rate limit are skipped

Audit log

.audit-off

nothing is written to audit.jsonl

Physical input

.physical-off

the dialog accepts injected keystrokes/clicks again

They are independent: turning off the deny lists does not silently turn off the dialog.

The markers are signed with guard.key (or COMPUTER_USE_GUARD_SECRET in the launcher's environment). A marker that is unsigned or hand-edited is ignored — the protection stays on — and the attempt is written to the audit log (op=guard_tamper) and surfaced in the next tool result. Anything that can write files in this directory can still read guard.key; see SECURITY.md §4.2 for the honest version of what that means.

Guard panel


Related MCP server: win-rdp-mcp

Layers of protection

Layer

What it does

Can the model bypass it?

Policy engine (policy.json)

Refuses to touch deny-listed processes / window titles, and refuses shells/LOLBins as launch_app targets. Optional allow-list. Rate limit. Applies to every batch step too.

The deny lists ignore confirm entirely. Editing policy.json widens them

Approval gate (approval.ps1)

Risky action → real dialog → waits for a human decision

Only a physical Alt+A / click counts. Not by confirm, not by injected input, not by posted messages (BM_CLICK), not by UIA InvokePattern, and not while another dialog is open

Gate lock (src/approval.js)

Refuses input-injecting tools while a dialog is open, re-checked after every await (including inside batch)

No — it is server-side state

Signed switches (src/guard.js)

Forged, hand-edited or replayed markers are ignored and reported

Cannot be forged or replayed without the key; guard.key is readable by your user, and the accepted-marker watermark can be rolled back by whoever can write it

Audit log (audit.jsonl)

Every action + its target process, redacted, hash-chained, with a chain head recording how far the segment got

Detects edits, deletions, truncation and hash-stripping (npm run audit:verify); a determined writer can still rewrite log and head together

Target resolution uses WindowFromPoint — which window a click actually lands on, not the foreground window. Actions with no coordinates (click, scroll at the cursor) resolve the real cursor position instead of falling back to the foreground window, and a drag is checked at both ends:

{ "blocked_by_policy": true, "reason": "target process is on the deny list",
  "detail": { "process": "ApplicationFrameHost", "title": "计算器",
              "matched": "applicationframehost" } }

What is on the lists

Four lists, all substring matches (case-insensitive), all in policy.json:

List

Behaviour

Default coverage

deny_processes (49)

hard refusal, no override

password managers, crypto wallets, regedit/diskmgmt/diskpart/gpedit

deny_window_titles (31)

hard refusal

password, bank, pay, wallet, 转账, 验证码, seed phrase, UAC

approval_processes (32)

every action pops the dialog

messaging (WeChat/QQ/Telegram/Slack…), mail, remote desktop (RDP/TeamViewer/AnyDesk…)

approval_window_titles (8)

every action pops the dialog

send, 发送, remote desktop

The split matters: a messaging app is not denied outright — you may want the agent to read or summarise it — but nothing is clicked there without you saying yes.

npm run test:policy checks the lists against 29 samples and fails on false positives (a browser, Notepad, Blender and this repo's own harness must all pass cleanly).


Install

Requirements: Windows 10/11, Node.js ≥ 18.

git clone https://github.com/be1st6666/guarded-computer-use-mcp
cd guarded-computer-use-mcp
npm install

Optional but recommended: PowerShell 7 (better UTF-8 and JSON handling). The server falls back to Windows PowerShell 5.1 automatically.

Optional: OCR needs uv on PATH. Everything else works without it.

Verify it works

npm test              # read-only tools; no side effects, safe to run any time
npm run test:unit     # unit tests for the policy/guard/audit/approval core
npm run test:smoke    # MCP handshake + tool schemas, no desktop needed
npm run test:policy   # the deny/approval lists, 29 samples
npm run test:typing   # type_text round-trip in its own temp Notepad window (skips if Notepad is open)
npm run test:inject   # shows the real dialog and proves injected input cannot answer it
npm run test:lock     # protocol-level: parallel tool calls cannot answer the dialog
npm run verify        # everything that does not need an interactive desktop

npm test prints a tick per tool plus its latency. If it lists tools and screenshot returns an image, the server is wired up correctly. npm run test:inject and npm run test:lock take over your screen for a few seconds (they open the real dialog) and must both end with all checks passed.

Configure your MCP client

{
  "mcpServers": {
    "computer": {
      "command": "node",
      "args": ["D:/path/to/guarded-computer-use-mcp/server.js"]
    }
  }
}

Add to $DSH_HOME/profiles/web/cordis.patch.yml:

- insert:
    - id: mcp-computer-use
      name: '@deepseek-ai/dsh-mcp-client'
      config:
        serverName: computer
        transport: stdio
        command: C:/Program Files/nodejs/node.exe
        args:
          - D:/path/to/guarded-computer-use-mcp/server.js

Tools appear as mcp__computer__<name>.


Performance

Measured on a 2560×1600 display, median of 5–8 runs:

Operation

Latency

Tokens returned

cursor_position / active_window

1 ms

7–39

ui_tree

12 ms

38

zoom region 480×150

25 ms

96

screen_hash

44 ms

9

screenshot 900×562

58 ms

674

screenshot 1600×1000

116 ms

2133

batch (3 steps + screenshot)

134 ms, one round trip

674

find_elements

209 ms

640

ocr (warm worker)

457 ms

554

The ~55 ms capture floor is the GPU→CPU readback of a full frame over GDI.

OCR latency scales with the number of recognised text boxes, not with the capture rectangle: a text-heavy full 2560×1600 screen measured ~6.9 s / 105 boxes, while a 1280×800 region measured ~3.3 s / 45 boxes (~2×). Downscaling the image first does not help — RapidOCR's detector normalises its input to a fixed size internally, so pre-scaling costs accuracy for almost no time — and a larger recognition batch is slower, not faster. So pass a region (x/y/width/height) instead of OCRing the whole screen whenever you do not need all of it.

Token economics

A screenshot costs ~2133 tokens. The alternatives cost far less:

Instead of a full screenshot

Tokens

Saving

screen_hash — "did anything change?"

9

237×

zoom — only the region you need

96

22×

find_elements — text, not pixels

640

3.3×

batch also collapses N actions into one model turn, which is the bigger win: a model turn costs 2–10 s of inference, a tool call costs 1–457 ms.


Three-tier targeting

Coordinates fail silently when a window moves. So try in order:

  1. find_elements / click_element — UI Automation. Clicks by name via InvokePattern (no mouse movement at all). Either finds the element or says it isn't there.

  2. ocr — no control tree, but there is text. RapidOCR (PaddleOCR models on ONNXRuntime, ~14 MB) reads it and returns screen-space boxes, so a recognised word can be clicked directly.

    OCR boxes

    Real output against the Windows Calculator: every digit located with a confidence score. The built-in Windows OCR engine returns zero words for this same region.

  3. screenshot + coordinates — last resort for canvas/self-drawn UI.

What the accessibility tree actually covers. It is easy to assume browsers expose nothing and reach for pixels too early. In practice Edge/Chromium does publish the page: a single find_elements on a 4399.com game index returned 22 hyperlinks with exact rects, including ones thousands of pixels offscreen — all clickable by name with no mouse movement.

What it still cannot see:

Accessible?

Static HTML links/buttons/inputs

yes

Native Win32 / WPF / UIA apps

yes

canvas / WebGL / game frames

no

Virtualised lists not yet mounted

no

Custom-drawn toolbars (many Chinese desktop apps)

no

When it is not, ocr and then plain coordinates are the fallbacks — in that order.

Measured on the same task (click a button):

Method

Latency

Tokens

Reliability

screenshot + vision + click

116 ms

2133+

medium

UIA semantic

309 ms

~700

high

OCR + click

459 ms

554

medium-high


Tools (26)

Group

Tools

Observe

screenshot zoom screen_hash wait_for_change cursor_position list_displays list_windows active_window clipboard_read

Semantic

find_elements click_element ui_tree

OCR

ocr

Mouse

mouse_move click drag scroll

Keyboard

type_text key hold_key

Window / launch

activate_window launch_app

Orchestration

batch wait

Other

clipboard_write bench

Coordinates are physical pixels of the virtual desktop. type_text injects Unicode per character via SendInput, so CJK, quotes and emoji go through verbatim with no escaping anywhere in the path.

Event-driven, not a video stream

Codex-style computer use is not a continuous stream either — it is act → screenshot → decide. Three primitives make that loop cheap:

  • screen_hash — 64×40 perceptual fingerprint, 44 ms, 9 tokens

  • wait_for_change — blocks until the screen actually changes; no polling from the model, no wasted turns

  • batch — [click, wait, screenshot] in one call, one round trip


Architecture

MCP client
   │  stdio, JSON-RPC
   ▼
server.js ──── one base64(UTF-8 JSON) line per request ────▶ host.ps1 (resident)
   ▲                                                              │
   └─────────── one base64(UTF-8 JSON) line per reply ◀──────────┘
                                                                  │
                                                    C# class Dsh (compiled once)
                                                                  │
                                              StretchBlt / SendInput / UIAutomation

File

Role

server.js

MCP server, 26 tools, policy + approval + audit

host.ps1

Resident PowerShell host + C# helper (must stay pure ASCII)

approval.ps1

The approval dialog

ocr.ps1

Windows OCR backend (Windows PowerShell 5.1 only — .NET Core has no WinRT projection)

ocr_rapid.py

RapidOCR backend, one-shot or --serve (warm worker, idle-exits)

policy.json

Deny lists, rate limit, approval settings

test-client.js

Standalone test client (read, uia, advanced, policy, rapid, …)

bench.js

Per-op latency and token benchmark

Design notes:

  • Resident host, compiled once. The C# helper is Add-Typed at startup, so a call costs 1–12 ms instead of 300–500 ms.

  • StretchBlt capture + downscale in one GDI call. Capture-then-resample spent 57 ms just on resampling — more than encoding.

  • JPEG by default. PNG encode of 1600×1000 costs 19–33 ms; JPEG q88 costs 4–8 ms and is half the size.

  • base64 transport. Every line on the wire is ASCII, sidestepping Windows PowerShell 5.1 console-encoding entirely.


Safety model in depth

What it protects against

  • The model deciding on its own to touch a password manager, banking or payment window → refused by policy, no override.

  • A destructive click (关闭 / Close / Delete / Send) or key chord (alt+f4, ctrl+w, win+*, shift+delete) → approval dialog.

  • The model answering its own approval dialog — a parallel tool call can no longer inject alt+a or click Allow: input tools are locked out while the dialog is open, and the dialog discards injected input entirely.

  • batch skipping the deny lists — every step is now policy-checked and audited individually.

  • Turning the guards off with a stray file — switches are signed; a forged or hand-edited marker is ignored and reported as guard_tamper.

  • Runaway loops → max_actions_per_minute.

  • "What did it actually do?" → audit.jsonl with the target process per action, sensitive argument values redacted, and a hash chain that makes quiet edits detectable (npm run audit:verify).

What it does not protect against

  • A mis-click in an app that is not on a deny list. If the model clicks the wrong thing in Notepad, nothing stops it.

  • A second desktop-control server, or any other local process, that can write files as you: it can replace guard.key, roll back guard.state.json / audit.head.json, widen policy.json, or run host.ps1 directly. It cannot answer the dialog — that needs a physical event — but it does not have to. See SECURITY.md §4.1.

  • Same-user file access: policy.json, guard.key and host.ps1 are all reachable by anything running as you.

  • It is not a sandbox. The agent runs with your user's privileges on your real desktop. There is no VM. "Control the real machine" and "full isolation" are architecturally mutually exclusive — Codex's sandbox works because it drives a desktop inside a VM, not yours.

  • Elevated windows: UIPI blocks input injection into admin windows, and the UAC secure desktop is unreachable. This is a Windows boundary, not a feature.


Risks and disclaimer

What can go wrong

This is not a toy permission. An agent driving this server can:

  • send a message, email or payment as you

  • delete or overwrite files it was never asked to touch

  • read whatever is on your screen, including other people's private data

  • change application or system settings

There is no undo. Ctrl+Z does not cover "sent", "paid" or "deleted".

Prompt injection

The agent reads your screen and the documents on it. Anything it reads can carry instructions: a web page, a PDF, an email, a chat message, a code comment. A hostile page can tell the agent to do something you never asked for.

The approval gate catches actions matching the safety patterns and the approval lists. It does not catch a plausible-looking click in an app that is on neither list. Treat everything the agent reads as untrusted input.

Your screen leaves your machine

Screenshots, OCR output, clipboard contents and window titles are sent to whichever model provider your MCP client uses. That is the whole point — the model has to see the screen — but it means:

  • everything visible while the agent runs is transmitted off-device

  • that includes other people's messages, documents and personal data

  • check your provider's data-retention policy before pointing this at anything sensitive

  • prefer zoom on a small region over a full screenshot when you can

OCR runs locally and sends nothing itself, but its output is returned to the model, so it is transmitted too.

What the guard does not do

  • It is not a sandbox. The agent runs as you, on your desktop, with your sessions and tokens.

  • It does not stop a wrong action in an app that is on neither list.

  • It does not survive anyone who can also edit policy.json or create the .guard-off marker — those are plain files in this directory.

  • The deny lists are substring matches: a speed bump, not a boundary.

You are responsible

You choose what to point this at, which lists to keep enabled, and whether to leave the approval gate on. Run it with the gate on until you have watched it work on your own machine. Do not expose the stdio transport to a network.

Provided under the MIT licence, without warranty of any kind — see LICENSE. The authors are not liable for any loss or damage arising from its use.


Known limits

  • Windows only.

  • ~55 ms per full screenshot — the GDI readback floor. A DXGI Desktop Duplication backend could cut it, at the cost of a native addon.

  • No continuous vision. By design; see the event-driven section.

  • OCR costs ~0.5–2.5 s depending on whether the warm worker is alive.

  • type_text needs focus — activate_window + click first.

  • The dialog needs a physical decision. If alt+a on the keyboard or a click on Allow does not approve it, the injected-input filter is not seeing your hardware as physical — run node src/guard.js set physical off (or untick 物理输入校验 in the panel) to fall back to ordinary button clicks, and please report it.

  • Anything that can write files as you can still win. It can replace guard.key, roll back guard.state.json / audit.head.json, edit policy.json, or run host.ps1 directly. The signing, the watermark and the chain head raise the bar and leave a trail; they are not a boundary.

  • The audit chain is tamper-evident, not tamper-proof. verify catches edits, a deleted tail, a missing file and stripped hashes against the chain head; a writer who rewrites the log and the head together is not detected.


Development

npm run verify                # lint + unit + policy + smoke + audit chain check
npm run test:unit             # unit tests: guard, audit, policy, approval lock
npm run test:smoke            # MCP handshake + tool schema smoke test (headless-safe)
npm run test:inject           # real dialog + injected Alt+A / click (needs a desktop)
npm run test:lock             # protocol-level gate-lock regression (needs a desktop)
npm test                      # read-only tools, no side effects
npm run test:uia              # accessibility tree + semantic search
npm run test:policy           # deny/approval lists, 29 samples, fails on false positives
npm run test:typing           # activate_window focus + multi-line/tab type_text
npm run bench                 # latency + token table
npm run audit:verify          # walk the audit hash chain, report edited/deleted records
npm run guard                 # print the four protection switches
node src/guard.js set guard off   # what the panel does under the hood (signed marker)
node test-client.js policy    # policy + audit behaviour end to end
node test-client.js rapid     # Windows OCR vs RapidOCR on the same region
node test-client.js newtools  # launch_app, approval gate, OCR-driven click

src/ holds the safety core as separate, unit-testable modules — guard.js (signed switches), audit.js (redaction + hash chain + rotation), policy.js (lists, rate limit, approval decision), approval.js (dialog + gate lock). server.js is the MCP wiring and the tool definitions.

test/ is the headless suite CI runs (unit tests + the MCP smoke test); e2e/ holds the two scripts that drive the real desktop (approval injection and the protocol-level gate-lock regression).

docs/make-*.ps1 regenerate the README figures from a live screen, so the screenshots can be kept honest rather than hand-drawn.

host.ps1 and ocr.ps1 must stay pure ASCII: Windows PowerShell 5.1 reads .ps1 as ANSI when there is no BOM, and a single non-ASCII byte can swallow a newline and corrupt the embedded C#. Verify with:

((Get-Content .\host.ps1 -AsByteStream) | Where-Object { $_ -gt 127 }).Count   # must be 0

approval.ps1, approval-toggle.ps1 and guard-panel.ps1 are the exception: they show Chinese to the user, so they are saved with a UTF-8 BOM, which both shells honour.

Contributing

Issues and PRs welcome. Three rules keep this repo reviewable:

  1. No third-party automation code. The whole point is that every line that touches your machine can be read in one sitting. host.ps1 is C# + Win32 and nothing else.

  2. Measure, don't claim. If you change something for speed, put a number in the PR — npm run bench exists for that.

  3. A security fix needs a test that fails without it. npm run test:inject and test/*.test.mjs are the examples; npm run verify must stay green.

Security-relevant behaviour is documented in SECURITY.md — if you change what a guard does, change that file in the same PR.

License

MIT — see LICENSE.

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