The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Embody
The most comprehensive MCP toolkit for TouchDesigner
Install
git clone https://github.com/dylanroscover/EmbodyInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Embody
create at the speed of thought.
embody.tools · Documentation · Manifesto · Changelog
Embot — he hops through your network while Envoy builds
Embody puts your ideas on screen as fast as you can describe them. Operators, connections, parameters, the works. Want to try a different direction? Spin up a new approach in seconds. Compare attempts side by side. Branch off the one that works. The tool keeps up with you, instead of the other way around.
Four Tools, One Idea
Envoy — forward velocity. An embedded MCP server lets Claude Code, Codex, OpenCode, Gemini, Cursor, Windsurf, and GitHub Copilot (via VS Code) talk directly to your live TouchDesigner session. Create operators, wire them up, set parameters, write extensions, debug errors — by saying what you want. No copy-pasting code. No describing your network in chat. Idea → operators in seconds.
Embody — lateral velocity. Tag any operator and Embody externalizes it to files on disk that mirror your network hierarchy. Try a new direction, branch off a good one, restore the state from yesterday — all in seconds. Your externalized files are the source of truth, so every project opens already in flow.
Convoy — outward velocity. Convoy-enabled Embody nodes on a trusted LAN discover, inspect, and control each other — one AI session relaying builds, test runs, saves, screenshots, files, and restarts to every machine in the room. A small per-user background app keeps each node reachable even while TouchDesigner is closed. Convoy guide
TDXN — the substrate that makes it all possible. TouchDesigner networks exported as human-readable YAML. The format is what lets your AI agent understand what's on the screen, what lets you diff one attempt against another, and what lets a network reconstruct itself from text on the next project open. TDXN is what makes the rest of this possible.
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