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 jingcheng-chen · MCP Server · ★ 1.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rhinomcp safe to install? View the security audit →
RhinoMCP Control Rhino 3D and Grasshopper with AI, in plain language. RhinoMCP connects Rhino to AI agents through the Model Context Protocol, so assistants like Claude and Cursor can model geometry, read your document, and build Grasshopper definitions for you, just by chatting. Quick start · What it can do · Usage · Examples · Tool reference English · 简体中文 Highlights Describe what you want and the assistant builds it in Rhino. It reads your document and can capture the viewport, so it works from what is actually on screen. It scripts Grasshopper for you: finding components, wiring them, setting sliders, and solving. A single plugin and a single config en
| Stars | 1,069 |
| Forks | 95 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64.94461026603/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-14 |
| Created | 2025-03-22 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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rhinomcp is RhinoMCP connects Rhino 3D to AI Agent through the Model Context Protocol (MCP). It is categorized as a MCP Server with 1.1k GitHub stars.
rhinomcp is primarily written in Python.
You can find installation instructions and usage details in the rhinomcp GitHub repository at github.com/jingcheng-chen/rhinomcp. The project has 1.1k stars and 95 forks, indicating an active community.
rhinomcp is released under the MIT license, making it free to use and modify according to the license terms.
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.
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