by posecode-dev · MCP Server · ★ 109
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
An open-source text language, parser, validator and Three.js renderer for inspectable 3D human movement.
| Stars | 109 |
| Forks | 9 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 57.6021176497055/100 |
| Open Issues | 9 |
| Last Updated | 2026-08-31 |
| Created | 2026-06-23 |
| Platforms | mcp, node |
| Est. Tokens | ~13k |
Looking for a posecode alternative? If you're comparing posecode with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Cheapest Money-Saving Self-hosted AI agent workspace with tool calling, MCP, multi-model routing, sandboxed ex
Connects MCP to major 3D printer APIs (Orca, FULU's Orca/Bambu, OctoPrint, Klipper, Duet, Repetier, Prusa, Cre
Open source version of Claude Managed Agents. Fastest way to build and deploy reliable AI agents, MCP tools an
Dynamically expose tools from proxied servers based on an Agent Persona
Official PostHog MCP Server 🦔
3D AI agent platform for the browser. Load any GLB/glTF avatar, give it an LLM brain with memory, emotions, an
Explore other popular mcp server tools:
posecode is An open-source text language, parser, validator and Three.js renderer for inspectable 3D human movement.. It is categorized as a MCP Server with 109 GitHub stars.
posecode is primarily written in TypeScript. It covers topics such as animation, dsl, dsl-syntax.
You can find installation instructions and usage details in the posecode GitHub repository at github.com/posecode-dev/posecode. The project has 109 stars and 9 forks, indicating an active community.
posecode is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to posecode on Agent Skills Hub include noobot, mcp-3D-printer-server, agentor. 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: