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 dddabtc · MCP Server · ★ 169
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is winremote-mcp safe to install? View the security audit →
WinRemote MCP — Run MCP Servers Remotely on Windows The ultimate Windows MCP server for remote desktop control and automation. Control any Windows machine through the Model Context Protocol — perfect for AI agents, Claude Desktop. Transform your Windows desktop into a powerful, remotely-accessible automation endpoint. Run on the Windows machine you want to control. Built with FastMCP and the Model Context Protocol. Quickstart (30 seconds) That's it! Your Windows MCP server is now running on and ready to accept commands from MCP clients like Claud
| Stars | 169 |
| Forks | 38 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.6661216934663/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-07 |
| Created | 2026-02-08 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~18k |
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winremote-mcp is Windows Remote MCP Server — 40+ tools for desktop automation, process management, file operations via FastMCP. It is categorized as a MCP Server with 169 GitHub stars.
winremote-mcp is primarily written in Python. It covers topics such as agent, automation, claude.
You can find installation instructions and usage details in the winremote-mcp GitHub repository at github.com/dddabtc/winremote-mcp. The project has 169 stars and 38 forks, indicating an active community.
winremote-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to winremote-mcp on Agent Skills Hub include oreilly-ai-agents, os-ai-computer-use, mcp-nixos. 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: