tdmcp

Pantani/tdmcp
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Install to Claude Code

claude mcp add tdmcp -- npx -y @dpantani/tdmcp

Summary

Pantani/tdmcp MCP server](https://glama.ai/mcp/servers/Pantani/tdmcp/badges/score.svg)](https://glama.ai/mcp/servers/Pantani/tdmcp) πŸ“‡ 🏠 🍎 πŸͺŸ - Stop wiring nodes by hand β€” describe a visual and the AI builds a real, playable TouchDesigner network:...

README.md

MindDesigner (tdmcp) β€” TouchDesigner MCP server

![CI](https://github.com/Pantani/tdmcp/actions/workflows/ci.yml) ![Docs](https://pantani.github.io/tdmcp/) ![npm version](https://www.npmjs.com/package/@dpantani/tdmcp) ![Node.js](https://nodejs.org) ![MCP server](https://modelcontextprotocol.io) ![License: MIT](LICENSE) ![tdmcp MCP server](https://glama.ai/mcp/servers/Pantani/tdmcp)

tdmcp is a Model Context Protocol (MCP) server for TouchDesigner β€” build TouchDesigner from plain language. You describe a visual to an AI assistant (Claude, Claude Code, Cursor, Codex); the AI builds the actual network of nodes inside your project, checks it for errors, and shows you a preview.

"Create a feedback tunnel from noise with blur and displace, then add bloom and output it to a window."

…and the nodes appear, wired up, in your /project1.

It works because it pairs two things every other tool was missing:

  • Real knowledge β€” an embedded reference of 629 operators, 68 Python classes,

workflow patterns, GLSL techniques and tutorials, so the AI uses real TouchDesigner operators instead of guessing.

  • Real execution β€” a small bridge running inside TouchDesigner that

actually creates, connects, inspects and previews nodes — with a create → verify → preview loop so the AI can see and fix its own work. Every generated network is auto-arranged into a readable left→right layout.

πŸ“– Documentation

Full guides and reference live on the docs site β†’ <https://pantani.github.io/tdmcp/>

| For artists / musicians | For developers | | --- | --- | | What is tdmcp? | Architecture | | Install (no terminal) | Tools reference | | Your first visual | Environment variables | | Shader Park | CLI & local copilot | | Prompt cookbook | Bridge & REST API | | Recipe gallery | Roadmap | | Troubleshooting | Deployment |

πŸ‡§πŸ‡· Portuguese documentation: <https://pantani.github.io/tdmcp/pt/>

How it works

Three pieces talk to each other on your computer:

   You + your AI            tdmcp server               TouchDesigner
  (Claude / Cursor)   ─▢   (a small program)    ─▢   (the bridge inside TD)
   "make a feedback                                      builds real nodes
    tunnel from noise"                                   in /project1
  1. Your AI assistant β€” where you type what you want.
  2. The tdmcp server β€” a small Node program that gives the AI a set of

TouchDesigner "tools" and the operator knowledge base. You install it once.

  1. The bridge β€” a tiny piece that runs inside TouchDesigner so the server

can actually drive it. You switch it on once per machine.

What you'll need

edition is fine.

  • An MCP-capable AI assistant: Claude Desktop (easiest), Claude Code,

Codex, or Cursor.

Node.js is only needed for the build-from-source path (Node 20+). The one-click Claude Desktop extension needs nothing extra β€” the server is bundled inside the .mcpb (formerly .dxt; legacy .dxt files still install).

Get started

You set up two sides: your AI (so it gets the tdmcp tools) and TouchDesigner (so the AI can drive it).

πŸ€– Easiest β€” let your AI install it. Using Claude Code, Codex, or Cursor? Paste this one message in:

Install and connect tdmcp for me using the official install guide:
https://pantani.github.io/tdmcp/guide/install
Do every step yourself; only stop when you need me to paste one line into TouchDesigner.

It clones, builds and wires everything up; the only manual step is pasting one line into TouchDesigner (Step 2 below).

🟒 Claude Desktop β€” one-click .mcpb (no terminal, no Node). Download tdmcp.mcpb, then in Claude Desktop open Settings β†’ Extensions and install it (drag it in or Install from file). Leave host/port at 127.0.0.1 / 9980. Full walkthrough: the install guide.

πŸ› οΈ Claude Code / Codex / Cursor β€” build from source.

git clone https://github.com/Pantani/tdmcp.git
cd tdmcp
npm run setup   # installs, builds, and prints the exact line to connect your client

Turn on the bridge inside TouchDesigner (everyone)

Open TouchDesigner, open the Textport (Dialogs β†’ Textport and DATs), paste this one line and press Enter:

import urllib.request; exec(urllib.request.urlopen("https://github.com/Pantani/tdmcp/raw/v0.11.0/td/bootstrap.py").read().decode())

You should see [tdmcp] bridge running on port 9980 (/project1/tdmcp_bridge). βœ… It's safe and reversible β€” it adds one tidy component; remove it later with from mcp import install; install.uninstall(). Other install methods (module path, terminal, reusable .tox) are in the bridge docs.

Make something

With TouchDesigner open and your AI connected, ask in plain language:

"Create an audio-reactive particle galaxy and show me a preview."

The AI builds the network, checks it for errors, and returns a thumbnail. Iterate: "make it warmer," "add a feedback trail," "output it fullscreen." More ideas in the prompt cookbook.

Not connecting? The two most common fixes: make sure the bridge is on (curl http://127.0.0.1:9980/api/info returns JSON), and restart your AI client after adding the server. Full troubleshooting.

What you can do

332 tools across three layers, plus library/packaging, AI session memory and Obsidian vault integrations β€” from one-line artist generators (create_feedback_network, create_audio_reactive, create_particle_system, create_generative_art, …) to building blocks (create_control_panel, animate_parameter, create_external_io for OSC/MIDI/DMX/NDI, …) down to atomic node CRUD and inspection. Many systems arrive already playable, with a control panel you can tweak, preset, or map to a controller. See the full, always-current tools reference and the recipe gallery.

Optional: Creative RAG

A local, opt-in creative repertoire of open-licensed artworks/artists/techniques the AI can search for inspiration. Off by default. Repertoire, not policy β€” no bridge, DMX or Python exec. Enable with TDMCP_RAG_ENABLED=1 plus a local Ollama install, then tdmcp creative-rag {sync|index|search}. Full guide: docs/CREATIVE_RAG.md.

Security

The bridge runs arbitrary Python inside your TD process and listens on port 9980 on all interfaces β€” treat it like an open door to that machine. Run it only on a trusted network, and for untrusted networks turn on bridge auth (TDMCP_BRIDGE_TOKEN) and/or disable the exec endpoints (TDMCP_BRIDGE_ALLOW_EXEC=0). Details: Security.

Links & community

  • Glama MCP directory β€” tdmcp's listing: <https://glama.ai/mcp/servers/Pantani/tdmcp>
  • awesome-touchdesigner β€” the community-curated TouchDesigner list: <https://github.com/monkeymonk/awesome-touchdesigner>
  • Docs site β€” <https://pantani.github.io/tdmcp/> Β· Roadmap β€” docs/ROADMAP.md

Contributing & development

Build with npm install && npm run build; run npm test, npm run typecheck, npm run lint. Work on the docs with npm run docs:dev (the tools reference is generated by scripts/gen-tool-docs.ts). See CONTRIBUTING.md, CHANGELOG.md, and the roadmap.

License

MIT β€” see LICENSE.

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