MCP server — control remote desktops via VNC with a native Swift daemon and Apple Vision OCR
io.github.ARAS-Workspace/claude-kvm MCP Server
Claude KVM is an MCP tool that controls remote desktop environments over VNC. It uses a thin JavaScript proxy layer (the MCP server) and a platform-native Swift VNC daemon, paired with Apple Vision OCR, as indicated by the repository description and readme excerpt.
🛠️ Key Features
VNC-based remote desktop control via MCP
Thin JS proxy layer for MCP server functionality
Native Swift VNC daemon component
Apple Vision OCR integration
🚀 Use Cases
Automating interaction with remote desktop environments
Building “computer-use” workflows that rely on VNC access
Adding OCR-based capabilities to remote desktop automation
⚡ Developer Benefits
MCP server interface for remote desktop control
Clear separation between JS proxy (MCP server) and Swift daemon
Topics covering automation, SSH, and Apple Silicon/macos-use
⚠️ Limitations
The provided source excerpt does not specify tool count, authentication, supported operating systems beyond macOS context, or explicit configuration details.
Claude KVM is an MCP tool that controls remote desktop environments over VNC. It consists of a thin JS proxy layer (MCP server) and a platform-native Swift VNC daemon running on your macOS system.
Phantom-WG could be a great alternative for you. Isolate your VNC server within your own network while enjoying self-hosted VPN performance with the extra privacy features you gain along the way.
Tests are conducted transparently on GitHub Actions — each step is visible in the CI environment. At the end of every test, whether the integration passes or fails, you'll find screenshots of each step the agent took during the session, along with an .mp4 video recording that captures the entire session. By reviewing these recordings and screenshots, you can observe how the agent progressed through each stage, how long the task took, and what decisions were made based on the system prompt. You can use these examples as a reference when crafting your own system prompts or instructions for the MCP server in your own environment.
WARNING
Artifacts attached to these runs may have expired due to GitHub's artifact retention policy. Persistent copies are prepared via the Persist Artifacts workflow and can always be accessed by run ID from the artifacts/ directory on the press-kit branch.
Architecture
graph TB
subgraph MCP["MCP Client (Claude)"]
AI["Claude"]
end
subgraph Proxy["claude-kvm · MCP Proxy (stdio)"]
direction TB
Server["MCP Server<br/><code>index.js</code>"]
Tools["Tool Definitions<br/><code>tools/index.js</code>"]
Server --> Tools
end
subgraph Daemon["claude-kvm-daemon · Native VNC Client (stdin/stdout)"]
direction TB
CMD["Command Handler<br/><i>PC Dispatch</i>"]
Scale["Display Scaling<br/><i>Scaled ↔ Native</i>"]
subgraph Screen["Screen"]
Capture["Frame Capture<br/><i>PNG · Crop · Diff</i>"]
OCR["OCR Detection<br/><i>Apple Vision</i>"]
end
subgraph InputGroup["Input"]
Mouse["Mouse<br/><i>Click · Drag · Move · Scroll</i>"]
KB["Keyboard<br/><i>Tap · Combo · Type · Paste</i>"]
end
VNC["VNC Bridge<br/><i>LibVNCClient 0.9.15</i>"]
CMD --> Scale
Scale --> Capture
Scale --> Mouse
Scale --> KB
Capture -.->|"framebuffer"| VNC
Mouse -->|"pointer events"| VNC
KB -->|"key events"| VNC
end
subgraph Target["Target Machine"]
VNC_Server["VNC Server<br/><i>:5900</i>"]
Desktop["Desktop Environment"]
VNC_Server --> Desktop
end
AI <-->|"stdio<br/>JSON-RPC"| Server
Server <-->|"stdin/stdout<br/>PC (NDJSON)"| CMD
VNC <-->|"RFB Protocol<br/>TCP :5900"| VNC_Server
classDef proxy fill:#1a1a2e,stroke:#16213e,color:#e5e5e5
classDef daemon fill:#0f3460,stroke:#533483,color:#e5e5e5
classDef target fill:#1a1a2e,stroke:#e94560,color:#e5e5e5
class Server,Tools proxy
class CMD,Scale,VNC,Capture,Mouse,KB daemon
class VNC_Server,Desktop target
Layers
Layer
Language
Role
Communication
MCP Proxy
JavaScript (Node.js)
Communicates with Claude over MCP protocol, manages daemon lifecycle
The VNC server's native resolution is scaled down to fit within --max-dimension (default: 1280px). Claude works more consistently with scaled coordinates — the daemon handles the conversion in the background:
code
Native: 4220 x 2568 (VNC server framebuffer)
Scaled: 1280 x 779 (what Claude sees and targets)
mouse_click(640, 400) → VNC receives (2110, 1284)
Screen Strategy
Claude minimizes token cost with a progressive verification approach:
code
diff_check → changeDetected: true/false ~5ms (text only, no image)
detect_elements → OCR text + bounding boxes ~50ms (text only, no image)
cursor_crop → crop around cursor ~50ms (small image)
screenshot → full screen capture ~200ms (full image)
detect_elements uses Apple Vision framework for on-device OCR. Returns text content with bounding box coordinates in scaled space — enables precise click targeting without consuming vision tokens.
Installation
Requirements
macOS (Apple Silicon / aarch64)
Node.js (LTS)
Daemon
bash
brew tap ARAS-Workspace/tap
brew install claude-kvm-daemon
NOTE
claude-kvm-daemon is compiled and code-signed via CI (GitHub Actions). The build output is packaged in two formats: a .tar.gz archive for Homebrew distribution and a .dmg disk image for notarization. The DMG is submitted to Apple servers for notarization within the same workflow — the process can be tracked from CI logs. The notarized DMG is available as a CI Artifact; the archived .tar.gz is also published as a release on the repository. Homebrew installation tracks this release.
The tool is end-to-end tested via CI — Claude executes tasks over VNC while an independent vision model observes and verifies the results. See the Integration Test for live workflow runs, system prompts, and demo recordings.
Configuration
MCP Proxy (ENV)
Parameter
Default
Description
VNC_HOST
127.0.0.1
VNC server address
VNC_PORT
5900
VNC port number
VNC_USERNAME
Username (required for ARD)
VNC_PASSWORD
Password
CLAUDE_KVM_DAEMON_PATH
claude-kvm-daemon
Daemon binary path (not needed if already in PATH)
CLAUDE_KVM_DAEMON_PARAMETERS
Additional CLI arguments for the daemon
Daemon Parameters (CLI)
Additional arguments passed to the daemon via CLAUDE_KVM_DAEMON_PARAMETERS:
{"result":{"detail":"OK — reset to defaults","timing":{"click_hold_ms":50,"combo_mod_ms":10,"cursor_crop_radius":150,"double_click_gap_ms":50,"drag_min_steps":10,"drag_pixels_per_step":20,"drag_position_ms":30,"drag_press_ms":50,"drag_settle_ms":30,"drag_step_ms":5,"hover_settle_ms":400,"key_hold_ms":30,"max_dimension":1280,"paste_settle_ms":30,"scroll_press_ms":10,"scroll_tick_ms":20,"type_inter_key_ms":20,"type_key_ms":20,"type_shift_ms":10},"scaledWidth":1280,"scaledHeight":779}}
All operations are performed through a single vnc_command tool:
Screen
Action
Parameters
Description
screenshot
Full screen PNG capture
cursor_crop
Crop around cursor with crosshair overlay
diff_check
Detect screen changes against baseline
set_baseline
Save current screen as diff reference
Mouse
Action
Parameters
Description
mouse_click
x, y, button?
Click (left|right|middle)
mouse_double_click
x, y
Double click
mouse_move
x, y
Move cursor
hover
x, y
Move + settle wait
nudge
dx, dy
Relative cursor movement
mouse_drag
x, y, toX, toY
Drag from start to end
scroll
x, y, direction, amount?
Scroll (up|down|left|right)
Keyboard
Action
Parameters
Description
key_tap
key
Single key press (enter|escape|tab|space|...)
key_combo
key or keys
Modifier combo ("cmd+c" or ["cmd","shift","3"])
key_type
text
Type text character by character
paste
text
Paste text via clipboard
Detection
Action
Parameters
Description
detect_elements
OCR text detection with bounding boxes (Apple Vision)
Returns text elements with bounding box coordinates in scaled space:
json
{"method":"detect_elements"}
json
{"result":{"detail":"13 elements","elements":[{"confidence":1,"h":9,"text":"Finder","w":32,"x":37,"y":6},{"confidence":1,"h":9,"text":"File","w":15,"x":84,"y":6},{"confidence":1,"h":9,"text":"Edit","w":19,"x":112,"y":6},{"confidence":1,"h":9,"text":"View","w":22,"x":143,"y":6},{"confidence":1,"h":11,"text":"Go","w":15,"x":179,"y":6},{"confidence":1,"h":9,"text":"Window","w":35,"x":207,"y":6},{"confidence":1,"h":11,"text":"Help","w":22,"x":255,"y":6},{"confidence":1,"h":11,"text":"8•","w":26,"x":1161,"y":6},{"confidence":1,"h":9,"text":"Fri Feb 20 22:19","w":80,"x":1189,"y":6},{"confidence":1,"h":9,"text":"Assets","w":32,"x":1202,"y":97},{"confidence":1,"h":9,"text":"Passwords.kdbx","w":74,"x":1181,"y":168},{"confidence":1,"h":93,"text":"PHANTOM","w":633,"x":322,"y":477},{"confidence":1,"h":32,"text":"YOUR SERVER, YOUR NETWORK, YOUR PRIVACY","w":629,"x":325,"y":568}],"scaledHeight":717,"scaledWidth":1280}}