Medium Risk

load_camera_preset

Load a saved camera preset and optionally animate to it

How to control load_camera_preset ↓

What load_camera_preset does on Threlte

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

Medium Risk

Why load_camera_preset needs a policy

This tool applies a saved camera preset to the scene, modifying the camera state. It is reversible (camera can be moved again) and does not delete data or execute arbitrary code, making Write the most appropriate category. Severity is medium since misuse could disrupt the user's scene view but causes no permanent damage.

From the tool's definition Load a saved camera preset and optionally animate to it

Documented attack patterns abuse exactly the kind of access load_camera_preset gives an agent:

How to control load_camera_preset

PolicyLayer is an MCP gateway — it sits between your AI agents and Threlte, and nothing reaches the server without passing your rules. This is the rule we recommend for load_camera_preset:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "load_camera_preset": {
      "limits": [
        {
          "counter": "load_camera_preset_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

load_camera_preset 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.

  1. Create a free account and register Threlte — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

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Related tools and policies

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Questions about load_camera_preset

What does the load_camera_preset tool do? +

Load a saved camera preset and optionally animate to it. It is categorised as a Write tool in the Threlte MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on load_camera_preset? +

Register the Threlte MCP server in PolicyLayer and add a rule for load_camera_preset: 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 Threlte. Nothing to install.

What risk level is load_camera_preset? +

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

Can I rate-limit load_camera_preset? +

Yes. Add a rate_limit block to the load_camera_preset 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 load_camera_preset completely? +

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

load_camera_preset is provided by the Threlte MCP server (serifeusstudio/threlte-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Threlte tool call.

Start from Threlte, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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30 Threlte tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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