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posecode-dev/posecode

posecode-dev/posecode

Text language for human movem
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add posecode -- npx -y posecode
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
119 ★ · posecode-dev/posecode · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 119 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 posecode-dev/posecode;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Posecode

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Kinematic motion as text.
An inspectable, editable movement format for animation tools, LLMs, and web products.
Like Mermaid for movement: small text documents for describing, validating, and rendering
deterministic human motion without hiding the source inside a black box.
Live Playground ·
Movement Library ·
Language Specification (SPEC.md) ·
LLM Authoring Guide ·
Examples ·
MCP Server
---
Why Posecode?
Animation clips and generated trajectories can show movement, but they often hide the semantic decisions that produced it.
Posecode keeps those decisions in readable source. A human can write the document, an animation tool can emit it, or an LLM can draft it. Parsing, validation, editing, and rendering do not require an AI model.
One .posecode document —
shoulders: abduct 160 ,
hips: abduct 30 ,
repeat 12 —
rendered live in the browser.
For example:
> Bend your knees, move your hips backward, and keep your chest upright.
A human may understand that instruction, but a renderer cannot reliably determine:
- which joints should move,
- by how many degrees,
- in which coordinate frame,
- over what duration,
- in what sequence,
- or within which physical limits.
Humans, tools, and language models all need a shared syntax for expressing movement in a renderable and testable form.
Posecode provides that missing representation.
See Posecode in 28 seconds
From readable movement source to validated 3D rendering, MCP tools, and a
one-script web embed.
▶ Watch the 28-second builder demo
Plain text in. Smooth, programmable 3D motion out.
Movement examples
pelvis: hinge — deadlift
knees: flex 95 — squat
shoulders: abduct 90 — lateral raise
---
Why Not Diffusion Text-to-Motion?
Neural text-to-motion systems can generate impressive movement, but they introduce problems for lightweight, programmable applications.
Resource intensive
Many systems require large models and GPU-backed inference, making real-time consumer deployment expensive.
Difficult to control
They usually produce coordinate trajectories rather than editable semantic instructions.
It is difficult to request a precise change such as:
> Reduce knee flexion by 10 degrees during the second phase.
Hard to validate
Black-box trajectories do not naturally expose readable joint rules, phase definitions, or range-of-motion limits.
Hard to debug
When a movement looks wrong, developers may not know which semantic instruction caused the problem.
---
The Posecode Approach
Posecode uses a lightweight, text-driven pipeline.
- **Readable:** movements are stored as small .posecode documents.
- **Structured:** joints, actions, angles, timings, and constraints are explicit.
- **Editable:** developers and models can modify individual movement properties.
- **Fast:** parsing and rendering happen client-side.
- **Deterministic:** the same Posecode input produces the same validated representation.
- **Inspectable:** parser warnings and fidelity checks explain problems.
- **Agent-friendly:** the MCP server exposes generation, validation, critique, and sharing tools.
- **Safety-aware:** authored and IK-generated angles are constrained by configured range-of-motion limits.
---
The Idea in 30 Seconds
A .posecode file describes movement as timed phases with targeted joint actions.
| 1. Write .posecode | 2. Render the movement |
| :--- | :--- |
| **posecode** exercise "Body-weight squat" **rig** humanoid **pose** start = standing **step** "Descend" 1.6s settle:   hips: flex 80   knees: flex 95   ankles: dorsiflex 14   ground-lock: feet   cue "Sit the hips back" **step** "Drive up" 1.2s drive:   hips: flex 0   knees: flex 0   ankles: dorsiflex 0   ground-lock: feet **repeat** 8 | |
---
> **OpenAI Build Week 2026:** Posecode existed before the hackathon. During Build Week, the project was extended using **Codex** — running on **GPT-5.6** — as the primary engineering tool for a real batch of shipped work: motion/grounding quality, language contract diagnostics, licensing restructuring, release automation, and product-facing pages. The sections below distinguish previous work from Build Week work using actual commit history, not a roadmap.
---
OpenAI Build Week Extension
What existed before Build Week
Before Build Week, Posecode already included:
- the core .posecode domain-specific language,
- a parser and intermediate motion representation,
- basic range-of-motion validation,
- a Three.js/WebGL renderer,
来源
awesome · https://github.com/posecode-dev/posecode
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