Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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.
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。
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。
选择你使用的 AI 应用,然后复制设置。
TDMCP_TOOL_PROFILE, TDMCP_RAW_PYTHON你需要
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。
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。
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。
TDMCP_TOOL_PROFILE envTDMCP_RAW_PYTHON env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。
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
注册名称已通过 GitHub 账户 Pantani 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
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。
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。
同一分类中有:Spec Driven Development, Remote Desktop Commander, ScienceShot science reference
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Sourced, citable answers in radiation and particle physics, photonics, electronics and quantum.
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。
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:
Full guides and reference live on the docs site → [https://pantani.github.io/tdmcp/](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 |
🇧🇷 Portuguese documentation: https://pantani.github.io/tdmcp/pt/
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
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.
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
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.
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
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.
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.
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.
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.
MIT — see LICENSE.