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 DmitriyGolub · MCP Server · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is threejs-devtools-mcp safe to install? View the security audit →
threejs-devtools-mcp MCP server for inspecting and modifying Three.js scenes in real time — 59 tools for objects, materials, shaders, textures, animations, performance monitoring, memory diagnostics, and code generation. Zero changes to your project. Works with vanilla Three.js, React Three Fiber, and any framework. Setup Add the MCP server Claude Code Claude Desktop Add to : Cursor Add to in your project: json { "mcpServers": { "threejs-devtools-mcp": { "command": "
| Stars | 85 |
| Forks | 9 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.9241558983973/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-07 |
| Created | 2026-03-15 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~133k |
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threejs-devtools-mcp is Three.js MCP server — inspect and edit scenes, materials, shaders, lights in real time from any AI agent. It is categorized as a MCP Server with 85 GitHub stars.
threejs-devtools-mcp is primarily written in TypeScript. It covers topics such as ai, claude-code, cursor.
You can find installation instructions and usage details in the threejs-devtools-mcp GitHub repository at github.com/DmitriyGolub/threejs-devtools-mcp. The project has 85 stars and 9 forks, indicating an active community.
threejs-devtools-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to threejs-devtools-mcp on Agent Skills Hub include vsync, agnix, Context-Engine. 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: