MindDesigner (tdmcp) — TouchDesigner MCP server

tdmcp is a Model Context Protocol (MCP) server
for TouchDesigner — 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 — 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 — 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.

📖 Documentation

Full guides and reference live on the docs site → https://pantani.github.io/tdmcp/

🇧🇷 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 — where you type what you want.
2. The tdmcp server — a small Node program that gives the AI a set of
   TouchDesigner "tools" and the operator knowledge base. You install it once.
3. The bridge — 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

• TouchDesigner — the free non-commercial
  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 — 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).

🤖 Easiest — 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 — one-click .mcpb (no terminal, no Node). Download
tdmcp.mcpb,
then in Claude Desktop open Settings → 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.

🛠️ Claude Code / Codex / Cursor — 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 → Textport and DATs), paste
this one line and press Enter:

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

You should see [tdmcp] bridge running on port 9980 (/project1/tdmcp_bridge). ✅
It's safe and reversible — 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

286 tools across three layers, plus library/packaging, AI session memory and
Obsidian vault integrations — 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.

Security

The bridge runs arbitrary Python inside your TD process and listens on port
9980 on all interfaces — 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.

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 — see LICENSE.