tdmcp — TouchDesigner MCP server MCP Server
io.github.Pantani/tdmcp
Build real TouchDesigner visuals from plain language with Claude, Cursor, or Codex.
What is the tdmcp — TouchDesigner MCP server MCP server?
The tdmcp MCP server is a bridge that lets AI assistants like Claude generate and control TouchDesigner networks in real time. You describe a visual effect in plain language, and the AI creates the actual nodes, wires them together, checks for errors, and shows you a preview—all from inside TouchDesigner.
tdmcp pairs AI with TouchDesigner by embedding knowledge of 629 operators and 68 Python classes, plus a live bridge that executes inside TouchDesigner. Instead of guessing at node names, the AI builds real networks, verifies them, and iterates based on previews. Artists and musicians can create audio-reactive systems, generative art, feedback loops, particle effects, and control panels by describing them in natural language.
How to install tdmcp — TouchDesigner MCP server
Copy-paste configuration for popular MCP clients.
TDMCP_TOOL_PROFILETool exposure profile. Glama and MCP directory scanners use directory for a compact build/inspect surface; choose full for the complete installed runtime or safe to hide destructive/raw-code tools.
TDMCP_RAW_PYTHONKeep client-authored Python escape-hatch tools hidden by default in registry scans; choose on only for a trusted local runtime.
Tools & capabilities
Tools this server exposes to the agent.
create_feedback_network— Generate a feedback tunnel with blur, displace, bloom, and outputcreate_audio_reactive— Build audio-reactive visual systemscreate_particle_system— Create particle-based generative effectscreate_generative_art— Generate algorithmic art networkscreate_control_panel— Build interactive control panels for parametersanimate_parameter— Animate and keyframe TouchDesigner parameterscreate_external_io— Set up OSC, MIDI, DMX, or NDI external I/ONode CRUD operations— Create, read, update, delete individual nodes and inspect their stateNetwork layout— Auto-arrange generated networks into readable left-to-right layouts
Use cases
- Create audio-reactive particle galaxies and feedback effects by describing them in plain language
- Build generative art systems with control panels that you can tweak, preset, or map to external controllers
- Generate shader-based visual effects and post-processing chains without manually wiring nodes
- Prototype interactive installations with OSC/MIDI/DMX/NDI integration
- Iterate on visual designs in real time by asking the AI to refine colors, timing, or complexity
tdmcp — TouchDesigner MCP server MCP server FAQ
tdmcp is an MCP server that lets you build TouchDesigner projects by describing them to Claude, Cursor, or Codex. The AI generates real node networks inside TouchDesigner, verifies them, and shows previews—no manual node wiring needed.
Yes. tdmcp is MIT-licensed open source. TouchDesigner's free non-commercial edition works fine.
Download tdmcp.mcpb from the latest GitHub release, open Claude Desktop Settings → Extensions, and install it (drag and drop or 'Install from file'). Leave host/port at 127.0.0.1/9980.
Clone the repo, run `npm run setup`, and follow the printed instructions to connect your client. Or paste the install guide URL into Claude Code and let it set up for you.
No API keys needed. You do need TouchDesigner installed and the bridge running inside it (one-click .tox component or one-line Textport command). The bridge listens on localhost:9980 by default.
The bridge runs Python inside TouchDesigner and listens on port 9980. Use it only on trusted networks. For untrusted networks, enable bridge auth with TDMCP_BRIDGE_TOKEN and/or disable exec endpoints with TDMCP_BRIDGE_ALLOW_EXEC=0.
README (reference)
Source of truth, from the repository.
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
- Your AI assistant — where you type what you want.
- 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.
- 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 extension file.
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 do the TouchDesigner bridge step.
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)
Easiest — no Textport. Download
tdmcp_bridge_package.tox
from the latest release, drag it into your /project1 network, and click
Install on the component. The package self-bootstraps and starts the bridge on
port 9980. ✅
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/v0.13.2/td/bootstrap.py").read().decode())
You should see [tdmcp] bridge running on port 9980 (/project1/tdmcp_bridge).
Either way 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, Palette package) 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/inforeturns JSON), and restart your AI client after adding the server. Full troubleshooting.
What you can do
508 tools across three layers, plus foundation primitives, CLI automation,
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.
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 — 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 — 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 — tdmcp's listing: https://glama.ai/mcp/servers/Pantani/tdmcp
- awesome-touchdesigner — the community-curated TouchDesigner list: https://github.com/monkeymonk/awesome-touchdesigner
- Docs site — https://pantani.github.io/tdmcp/ · Roadmap — 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 — see LICENSE.
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