learn_control

EXPERIMENTAL two-step

SERVERtdmcp — TouchDesigner MCP server SOURCE@dpantani/tdmcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pantani-tdmcp/learn-control.md

WHAT IT DOES

What learn_control does on tdmcp — TouchDesigner MCP server

AI agents use learn_control to create or update resources in tdmcp — TouchDesigner MCP server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your tdmcp — TouchDesigner MCP server environment.

RISK

Why learn_control is rated Medium

An AI agent can call learn_control faster than any human can review: one bad instruction and it creates or modifies resources in tdmcp — TouchDesigner MCP server by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs learn_control safely

PolicyLayer is an MCP gateway: it sits between your AI agents and tdmcp — TouchDesigner MCP server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For learn_control, this is the rule to start with:

learn_control Rate-limited

learn_control stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "learn_control": {
      "limits": [
        {
          "counter": "learn_control_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect tdmcp — TouchDesigner MCP server, apply this rule, and every learn_control call is checked against it from then on.

FAQ

Questions about learn_control

What does the learn_control tool do? +

EXPERIMENTAL two-step. It is categorised as a Write tool in the tdmcp — TouchDesigner MCP server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on learn_control? +

Register the tdmcp — TouchDesigner MCP server MCP server in PolicyLayer and add a rule for learn_control: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches tdmcp — TouchDesigner MCP server. Nothing to install.

What risk level is learn_control? +

learn_control is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit learn_control? +

Yes. Add a rate_limit block to the learn_control rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block learn_control completely? +

Set action: deny in the PolicyLayer policy for learn_control. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides learn_control? +

learn_control is provided by the tdmcp — TouchDesigner MCP server MCP server (@dpantani/tdmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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