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  3. Claude KVM
Claude KVM logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 11:01:58 AM

Claude KVM

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository16 GitHub StarsTotal stargazers on GitHub for the source repository (16 stars).Visit Website

MCP server β€” control remote desktops via VNC with a native Swift daemon and Apple Vision OCR

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "claude-kvm": {
      "command": "npx",
      "args": [
        "-y",
        "claude-kvm"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

Claude KVM

Claude KVM

Remote Access, Artificial Intelligence

claude-kvm.ai

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.

Claude KVM Demo Claude KVM Demo Mac

[!TIP] 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.

Live Test Runs

  • Integration Test
  • Mac Integration Test
  • Mac Calculator Test
  • Mac Scientific Calculator Test
  • Mac Safari Browsing Test
  • Mac Drag & Drop Test
  • Mac Chess Test
  • Mac Chess Direct Test
  • Mac Phantom-WG Install Test

[!NOTE] Tests are conducted transparently on GitHub Actions β€” 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

mermaid
graph TB
    subgraph MCP["MCP Client (Claude)"]
        AI["Claude"]
    end

    subgraph Proxy["claude-kvm Β· 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 Β· 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 Β· Crop Β· Diff</i>"]
            OCR["OCR Detection<br/><i>Apple Vision</i>"]
        end

        subgraph InputGroup["Input"]
            Mouse["Mouse<br/><i>Click Β· Drag Β· Move Β· Scroll</i>"]
            KB["Keyboard<br/><i>Tap Β· Combo Β· Type Β· 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

LayerLanguageRoleCommunication
MCP ProxyJavaScript (Node.js)Communicates with Claude over MCP protocol, manages daemon lifecyclestdio JSON-RPC
VNC DaemonSwift/C (Apple Silicon)VNC connection, screen capture, mouse/keyboard input injectionstdin/stdout PC (NDJSON)

PC (Procedure Call) Protocol

Communication between the proxy and daemon uses the PC protocol over NDJSON:

Code
Request:      {"method":"<name>","params":{...},"id":<int|string>}
Response:     {"result":{...},"id":<int|string>}
Error:        {"error":{"code":<int>,"message":"..."},"id":<int|string>}
Notification: {"method":"<name>","params":{...}}

Coordinate Scaling

The VNC server's native resolution is scaled down to fit within --max-dimension (default: 1280px). Claude works more consistently with scaled coordinates β€” 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) β†’ VNC receives (2110, 1284)

Screen Strategy

Claude minimizes token cost with a progressive verification approach:

Code
diff_check       β†’  changeDetected: true/false     ~5ms    (text only, no image)
detect_elements  β†’  OCR text + bounding boxes      ~50ms   (text only, no image)
cursor_crop      β†’  crop around cursor              ~50ms   (small image)
screenshot       β†’  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 β€” 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 β€” 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.

  • Release Β· Source Code
  • LibVNC Build Β· LibVNC Branch
  • Homebrew Tap

MCP Configuration

Create a .mcp.json file in your project directory:

config.json
{
  "mcpServers": {
    "claude-kvm": {
      "command": "npx",
      "args": ["-y", "claude-kvm"],
      "env": {
        "VNC_HOST": "192.168.1.100",
        "VNC_PORT": "5900",
        "VNC_USERNAME": "user",
        "VNC_PASSWORD": "pass",
        "CLAUDE_KVM_DAEMON_PATH": "/opt/homebrew/bin/claude-kvm-daemon",
        "CLAUDE_KVM_DAEMON_PARAMETERS": "-v"
      }
    }
  }
}

[!NOTE] The tool is end-to-end tested via CI β€” 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)

ParameterDefaultDescription
VNC_HOST127.0.0.1VNC server address
VNC_PORT5900VNC port number
VNC_USERNAMEUsername (required for ARD)
VNC_PASSWORDPassword
CLAUDE_KVM_DAEMON_PATHclaude-kvm-daemonDaemon binary path (not needed if already in PATH)
CLAUDE_KVM_DAEMON_PARAMETERSAdditional CLI arguments for the daemon

Daemon Parameters (CLI)

Additional arguments passed to the daemon via CLAUDE_KVM_DAEMON_PARAMETERS:

Code
"CLAUDE_KVM_DAEMON_PARAMETERS": "--max-dimension 800 -v"

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
16
Stargazers on the source repository.
npm downloads
449
Package downloads in the last 30 days.
Last commit
2mo ago
Most recent push to the default branch.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Claude KVM

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "claude-kvm": { "command": "npx", "args": ["-y","claude-kvm"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedJul 6, 2026
11/15 checks healthy over the last 45d
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars16
GitHub Star CountTotal stargazers on GitHub representing community popularity (16 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 6, 2026
npm downloads449/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
44Quality signal: Fair Β· 44/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 2d ago via OSV.dev Β· claude-kvm (npm)

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