No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by hrrrsn · MCP Server · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-vnc safe to install? View the security audit →
💻 mcp-vnc A Model Context Protocol (MCP) server that enables AI agents to remotely control Windows, Linux, macOS or anything else that can run a VNC server (don't worry, it's probably fine). 🚀 Quick Start Install from NPM Install from Source ⚙️ Configuration Claude Desktop Locate and open your Claude Desktop configuration file: macOS: Windows: Linux: Add the following configuration: Using NPM Install: Built from Source: json { "mcpServers": { "vnc-controller": { "type": "stdio",
| Stars | 56 |
| Forks | 11 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.9637638711994/100 |
| Open Issues | 17 |
| Last Updated | 2026-09-02 |
| Created | 2025-06-22 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
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mcp-vnc is Remote desktop control for AI. It is categorized as a MCP Server with 56 GitHub stars.
mcp-vnc is primarily written in TypeScript. It covers topics such as mcp-server, remote-control, vnc.
You can find installation instructions and usage details in the mcp-vnc GitHub repository at github.com/hrrrsn/mcp-vnc. The project has 56 stars and 11 forks, indicating an active community.
mcp-vnc is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-vnc on Agent Skills Hub include ai-security-tool, zedra, VibeBridge. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: