touchdesigner-mcp-server: Agent for Claude Code

.claude/agents/research-experimental.md

research-experimental is an agent for Claude Code from bottobot/touchdesigner-mcp-server. It costs 18 tokens per session (707 once invoked), scanned A, original, MIT.

An agent for researching experimental techniques in TouchDesigner, a tool for creating interactive visuals and multimedia systems. The listed topics include GLSL shaders, GPU computing, machine learning, generative systems, audio-visual work, networking, and advanced Python.

In plain words
What is it for?
Use it to document experimental techniques, code examples, relevant operators, performance notes, and version information in structured wiki data.
Why use it?
It helps organize research about newer or less-established TouchDesigner methods in a knowledge base.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is bottobot/touchdesigner-mcp-server's own configuration. It tells Claude Code how to work on touchdesigner-mcp-server itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything touchdesigner-mcp-server configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /home/robert/Documents/TD-MCP/touchdesigner-mcp-server.

Reuse

Borrowing it

Nothing to install: this file belongs to bottobot/touchdesigner-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/bottobot/touchdesigner-mcp-server/main/.claude/agents/research-experimental.md
Clone the repo
git clone --depth 1 https://github.com/bottobot/touchdesigner-mcp-server

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for research-experimental

README.md
[![agentmods](https://agentmods.dev/badge/agents/bottobot/touchdesigner-mcp-server/research-experimental/github.svg)](https://agentmods.dev/agents/bottobot/touchdesigner-mcp-server/research-experimental)
Your own site
<a href="https://agentmods.dev/agents/bottobot/touchdesigner-mcp-server/research-experimental"><img src="https://agentmods.dev/badge/agents/bottobot/touchdesigner-mcp-server/research-experimental/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research-experimental

Your own site · 80×15
<a href="https://agentmods.dev/agents/bottobot/touchdesigner-mcp-server/research-experimental"><img src="https://agentmods.dev/badge/agents/bottobot/touchdesigner-mcp-server/research-experimental.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 707 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.00707
Opus 5.5 $0.00007 $0.00283
Sonnet 5.5 $0.00004 $0.00141
Haiku 4.5 $0.00002 $0.00071

Measured 1mo ago against content hash 25a303e9ec92, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

research-experimental scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/research-experimental.md · 77 lines

What it actually says

You are researching and documenting cutting-edge experimental TouchDesigner techniques for the MCP server knowledge base.

Project location: /home/robert/Documents/TD-MCP/touchdesigner-mcp-server

First, read these existing files for context:

  1. /wiki/data/python-api/glslTOP.json or /wiki/docs/python/glslTOP_Class.htm — GLSL TOP API
  2. Any script/compute TOP references in the project
  3. /wiki/data/tutorials/ directory — see what tutorials exist

Then create /wiki/data/experimental/ directory with these comprehensive data files:

a) /wiki/data/experimental/index.json: { "categories": ["glsl", "gpu-compute", "machine-learning", "generative-systems", "audio-visual", "networking", "python-advanced"], "totalTechniques": 0, "lastUpdated": "2026-02-21" }

b) /wiki/data/experimental/glsl.json — GLSL techniques: At minimum include these techniques with full detail:

  • Raymarching / SDF rendering in GLSL TOP
  • Reaction-diffusion systems via GLSL
  • Feedback loop patterns (GLSL + Feedback TOP)
  • Custom post-processing pipelines
  • Procedural texture generation For each technique provide: name, description, operators[], codeExample (real GLSL code), performance (low/medium/high), versionRequirement, useCases[], relatedTechniques[]

c) /wiki/data/experimental/gpu-compute.json — GPU compute patterns:

  • Script TOP for GPU buffer operations
  • CUDA integration patterns
  • Shared memory TOP/CHOP patterns
  • GPU instancing via Geometry COMP
  • Particle systems using compute shaders

d) /wiki/data/experimental/machine-learning.json — ML integration:

  • TouchEngine CHOP/TOP for ML models
  • ONNX model integration
  • Stable Diffusion via Script TOP
  • Real-time pose estimation (MediaPipe patterns)
  • Audio ML (classification, generation)
  • Version requirement: 2022+ for TouchEngine

e) /wiki/data/experimental/generative-systems.json — generative art techniques:

  • L-system implementations in SOPs
  • Cellular automata via DAT + Script
  • Strange attractors (Lorenz, Rössler) in CHOPs
  • Agent-based systems using Replicator COMP
  • Recursive network patterns

f) /wiki/data/experimental/audio-visual.json — audio-visual synthesis:

  • FFT analysis to geometry (CHOP to SOP)
  • Granular synthesis patterns
  • MIDI-driven visual generation
  • Spectral analysis visualization
  • Beat detection algorithms

g) /wiki/data/experimental/networking.json — multi-system networking:

  • TouchDesigner OSC server/client setup
  • WebSocket DAT for browser integration
  • NDI video streaming patterns
  • Shared memory CHOP/TOP for inter-process
  • Multi-instance synchronization via TDAbleton

h) /wiki/data/experimental/python-advanced.json — advanced Python in TD:

  • Asyncio patterns in TD (run() coroutines)
  • Custom extensions (tdu.Dependency)
  • Python threading with callbacks
  • External library integration (numpy, scipy, opencv)
  • Custom DAT operators

Update /wiki/data/experimental/index.json with accurate totalTechniques count after creating all files.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 77 lines · 18 tokens per session scan A 25a303e9ec92

Subscribe to this mod's changes

research-experimental is an agent published in the GitHub repository bottobot/touchdesigner-mcp-server (80 stars, last pushed 28d ago), licensed MIT. It adds 18 tokens to every session and 707 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other agents, from other repositories

td-surveyor

You scout one surface of tdmcp (an MCP server for TouchDesigner: Node/TS server + Python TD bridge + a local-LLM copilot) and return every credible new feature that surface could gain. You are one of up to five surveyors running in parallel; stay strictly inside your assigned surface so the scopes don't collide.…

Pantani/tdmcp · 109 tokens

frontend-reviewer

Reviews interface, branding and copy. Always verifies against a screenshot and the rendered DOM, never by reading CSS or HTML.

everywan-dev/claude-code-engineering · 28 tokens

vkm-implementer

Terse minimal-diff executor for well-specified implementation tasks. Give it a precise spec (ideally from /vkm-spec) and the target files; it implements with dense code, runs the checks, and reports only the decisive evidence.

Vahlame/create-vkm-kit · 55 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens