semantic_model.bind

Bind Blender objects and references to one stable semantic component ID.

SERVERVisionmcp SOURCEjoshuahickscorp/visionmcp

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/visionmcp/semantic-model.bind.md

WHAT IT DOES

What semantic_model.bind does on Visionmcp

AI agents use semantic_model.bind to create or update resources in Visionmcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Visionmcp environment.

RISK

Why semantic_model.bind is rated Medium

This tool creates or modifies a binding between Blender objects and a semantic component ID, which is a reversible write operation that associates data/references with an identifier. It does not execute code, delete data, or involve financial transactions.

From the tool's definition Bind Blender objects and references to one stable semantic component ID

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs semantic_model.bind safely

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

semantic_model.bind Rate-limited

semantic_model.bind 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": {
    "semantic_model.bind": {
      "limits": [
        {
          "counter": "semantic_model.bind_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 Visionmcp, apply this rule, and every semantic_model.bind call is checked against it from then on.

FAQ

Questions about semantic_model.bind

What does the semantic_model.bind tool do? +

Bind Blender objects and references to one stable semantic component ID. It is categorised as a Write tool in the Visionmcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on semantic_model.bind? +

Register the Vision MCP server in PolicyLayer and add a rule for semantic_model.bind: 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 Visionmcp. Nothing to install.

What risk level is semantic_model.bind? +

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

Can I rate-limit semantic_model.bind? +

Yes. Add a rate_limit block to the semantic_model.bind 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 semantic_model.bind completely? +

Set action: deny in the PolicyLayer policy for semantic_model.bind. 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 semantic_model.bind? +

semantic_model.bind is provided by the Vision MCP server (joshuahickscorp/visionmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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