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tdmcp — TouchDesigner MCP server

作者:Pantani版本 0.13.2i★ –i在你的电脑上运行
注册名称io.github.Pantani/tdmcp

安装

概览

作者提供的说明(英文原文)

Build real visual systems in TouchDesigner from plain language with Claude, Cursor or Codex.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: TDMCP_TOOL_PROFILE, TDMCP_RAW_PYTHON

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "tdmcp": {
      "command": "npx",
      "args": [
        "-y",
        "@dpantani/tdmcp"
      ],
      "env": {
        "TDMCP_TOOL_PROFILE": "your-value",
        "TDMCP_RAW_PYTHON": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add tdmcp --env TDMCP_TOOL_PROFILE=your-value --env TDMCP_RAW_PYTHON=your-value -- npx -y @dpantani/tdmcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "tdmcp": {
      "command": "npx",
      "args": [
        "-y",
        "@dpantani/tdmcp"
      ],
      "env": {
        "TDMCP_TOOL_PROFILE": "your-value",
        "TDMCP_RAW_PYTHON": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "tdmcp": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@dpantani/tdmcp"
      ],
      "env": {
        "TDMCP_TOOL_PROFILE": "your-value",
        "TDMCP_RAW_PYTHON": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • TDMCP_TOOL_PROFILE env
    Tool 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_PYTHON env
    Keep client-authored Python escape-hatch tools hidden by default in registry scans; choose on only for a trusted local runtime.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 Pantani 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 18345 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 18345 个服务器的 20% 更新
  • 基础检查结果等于或优于此分类中其他 18345 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

tdmcp — TouchDesigner MCP server 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.13.2)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, ScienceShot science reference

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

ScienceShot science reference

作者:scienceshot.com

Sourced, citable answers in radiation and particle physics, photonics, electronics and quantum.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

MindDesigner (tdmcp) — TouchDesigner MCP server

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/](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](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:

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.

🛠️ 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. ✅

Prefer a one-line Textport command?

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/info returns JSON), and **restart your AI

client** after adding the server. Full

troubleshooting.

What you can do

509 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

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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