tdmcp
# MindDesigner (tdmcp) — TouchDesigner MCP server
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**tdmcp is a [Model Context Protocol](https://modelcontextprotocol.io) (MCP) server
for [TouchDesigner](https://derivative.ca)** — 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/>**
| For artists / musicians | For developers |
| --- | --- |
| [What is tdmcp?](https://pantani.github.io/tdmcp/guide/what-is-tdmcp) | [Architecture](https://pantani.github.io/tdmcp/reference/architecture) |
| [Install (no terminal)](https://pantani.github.io/tdmcp/guide/install) | [Tools reference](https://pantani.github.io/tdmcp/reference/tools) |
| [Your first visual](https://pantani.github.io/tdmcp/guide/first-visual) | [Environment variables](https://pantani.github.io/tdmcp/reference/environment) |
| [Shader Park](https://pantani.github.io/tdmcp/guide/shader-park) | [CLI & local copilot](https://pantani.github.io/tdmcp/reference/cli) |
| [Prompt cookbook](https://pantani.github.io/tdmcp/guide/prompt-cookbook) | [Bridge & REST API](https://pantani.github.io/tdmcp/reference/bridge-api) |
| [Recipe gallery](https://pantani.github.io/tdmcp/guide/recipes) | [Roadmap](docs/ROADMAP.md) |
| [Troubleshooting](https://pantani.github.io/tdmcp/guide/troubleshooting) | [Deployment](docs/DEPLOYMENT.md) |
🇧🇷 **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](https://derivative.ca/download)** — 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+](https://nodejs.org)**).
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:
```text
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](https://github.com/Pantani/tdmcp/releases/latest/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](https://pantani.github.io/tdmcp/guide/install).
**🛠️ Claude Code / Codex / Cursor — build from source.**
```bash
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**](https://github.com/Pantani/tdmcp/releases/latest/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. ✅
<details>
<summary>Prefer a one-line Textport command?</summary>
Open the **Textport** (`Dialogs → Textport and DATs`), paste this **one line** and
press Enter:
```python
import urllib.request; exec(urllib.request.urlopen("https://github.com/Pantani/tdmcp/raw/v0.13.1/td/bootstrap.py").read().decode())
```
You should see `[tdmcp] bridge running on port 9980 (/project1/tdmcp_bridge)`.
</details>
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](https://pantani.github.io/tdmcp/reference/bridge-api).
### 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](https://pantani.github.io/tdmcp/guide/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](https://pantani.github.io/tdmcp/guide/troubleshooting).
## What you can do
**507 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](https://pantani.github.io/tdmcp/reference/tools) and the
[recipe gallery](https://pantani.github.io/tdmcp/guide/recipes).
## 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](https://ollama.com) install, then `tdmcp creative-rag {sync|index|search}`.
Full guide: [docs/CREATIVE_RAG.md](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](https://pantani.github.io/tdmcp/reference/architecture#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](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](https://pantani.github.io/tdmcp/reference/tools) is generated by
`scripts/gen-tool-docs.ts`). See [CONTRIBUTING.md](CONTRIBUTING.md),
[CHANGELOG.md](CHANGELOG.md), and the [roadmap](docs/ROADMAP.md).
## License
MIT — see [LICENSE](LICENSE).
TDQS
Scored across 507 tools
With 507 tools, many have heavily overlapping purposes: dozens of create_*_reactive variants, create_*_bus / connect_*_bridge scaffolds for the same external systems (QLab, Resolume, OBS), and multiple raymarching/SDF/scene builders. Even detailed descriptions cannot prevent an agent from frequently picking the wrong near-duplicate tool.
The dominant pattern is verb_noun snake_case (create_*, get_*, set_*, manage_*), which is fairly consistent. However, there are notable deviations like macro_recorder, one_source_five_ways, generative_classics_pack, and project_documentation_site, plus several interchangeable verbs (create/build/make/setup/scaffold/connect) for similar actions.
507 tools is an extreme outlier, far beyond even the 50+ threshold for a 1. This makes the server overwhelming, context-heavy, and impractical for an agent to navigate. A TouchDesigner server of this scope would still be far too large at 100+ tools.
The tool surface is extraordinarily comprehensive, covering node CRUD, parameter lifecycle, network inspection, packaging, recipes, vault integration, external integrations, and many generative builders. Minor gaps exist (e.g., no explicit project-open/load tool, many scaffolds are non-functional stubs), but the breadth is remarkable.