MindDesigner / tdmcp: an MCP server that builds real TouchDesigner networks from plain language

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MindDesigner / tdmcp: an MCP server that builds real TouchDesigner networks from plain language

Hi everyone,

I wanted to share a project I have been building: MindDesigner (tdmcp), an open-source MCP server for TouchDesigner.

The goal is simple: let an MCP-capable AI assistant build actual TouchDesigner networks from plain language, not just search documentation.

For example, you can ask:

Create an audio-reactive particle galaxy with a warm feedback trail, expose the main controls, check it for errors, and show me a preview.

tdmcp connects three things locally:

  • your AI assistant: Claude Desktop, Claude Code, Codex, Cursor, etc.
  • the MCP server: exposes TouchDesigner-aware tools to the assistant
  • a small bridge running inside TouchDesigner: creates, connects, inspects, edits, and previews real operators in your project

What I am trying to solve is the gap between “the AI knows some TouchDesigner words” and “the AI can actually operate inside TouchDesigner safely enough to be useful.”

Current highlights:

  • embedded TouchDesigner knowledge base: 629 operators, 68 Python classes, workflow patterns, GLSL techniques, and tutorials
  • 179 MCP tools, from high-level artist tools like feedback networks, audio-reactive systems, particles, Shader Park scenes, and live/VJ utilities down to low-level node CRUD and inspection
  • create → verify → preview loop, so the assistant can build something, inspect it, catch errors, and iterate
  • auto-arranged readable networks instead of random node piles
  • Claude Desktop .mcpb bundle for no-terminal install
  • source setup for Claude Code, Codex, Cursor, and other MCP clients
  • project analysis, generated README/docs, reusable components, presets, recipes, and Obsidian vault integration
  • security controls for the local bridge, including bearer-token auth and the option to disable arbitrary exec endpoints

It is still moving fast, but it is already usable. The project is not affiliated with Derivative; it is a community experiment in making TouchDesigner more AI-native while still keeping the actual patch visible, editable, and artist-owned.

Links:

I would love feedback from TouchDesigner users, especially around:

  • what workflows would actually be useful in production or live performance
  • where the bridge should be more careful or transparent
  • which TouchDesigner concepts AI assistants still misunderstand
  • what examples, recipes, or tutorials would make this easier to evaluate

If anyone here is experimenting with MCP, AI-assisted patching, documentation agents, or live-control workflows, I would be very happy to compare notes.

Thanks!

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