Text-based language and MCP server for describing, validating, and rendering deterministic 3D human motion.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
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๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Posecode.
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 ยท Movement Library ยท Language Specification ยท Examples ยท MCP Server
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 โ
shoulders: abduct 160,
hips: abduct 30,
repeat 12 โ
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:
Humans, tools, and language models all need a shared syntax for expressing movement in a renderable and testable form.
Posecode provides that missing representation.
From readable movement source to validated 3D rendering, MCP tools, and a one-script web embed.
โถ Watch the 28-second builder demo
Plain text in. Smooth, programmable 3D motion out.
pelvis: hinge โ deadlift
|
knees: flex 95 โ squat
|
shoulders: abduct 90 โ lateral raise
|
Neural text-to-motion systems can generate impressive movement, but they introduce problems for lightweight, programmable applications.
Many systems require large models and GPU-backed inference, making real-time consumer deployment expensive.
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.
Black-box trajectories do not naturally expose readable joint rules, phase definitions, or range-of-motion limits.
When a movement looks wrong, developers may not know which semantic instruction caused the problem.
Posecode uses a lightweight, text-driven pipeline.
.posecode documents.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 humanoidpose start = standingstep "Descend" 1.6s settle:ย ย hips: flex 80ย ย knees: flex 95ย ย ankles: dorsiflex 14ย ย ground-lock: feetย ย cue "Sit the hips back"step "Drive up" 1.2s drive:ย ย hips: flex 0ย ย knees: flex 0ย ย ankles: dorsiflex 0ย ย ground-lock: feetrepeat 8 | ![]() |
OpenAI Build Week 2026: Posecode existed before the hackathon. During Build Week, the project was extended using Codex โ running on GPT-5.6 โ 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.
Before Build Week, Posecode already included:
.posecode domain-specific language,This original version was developed primarily with Claude as an AI-assisted engineering tool.
That prior work provides the foundation for the project, but it is not presented as the new hackathon contribution.
Every item below is a merged, dated pull request built with Codex (GPT-5.6) โ see Build Week Evidence for direct links.
drive/settle/flow/snap), a parser validation CLI, and embed compatibility metadata (#62)./for-products page documenting the web component, parser, renderer, and MCP server for integrators (#82, #74).Factual signals from GitHub, npm, and our automated checks โ not a rating.
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