Low Risk

tm_render_image

Render a still preview image of the model at a specified resolution by pulling the APS Model Derivative thumbnail (capped at 800x800 by the APS endpoint). Also resolves the camera_preset against model metadata to identify which 3D view it maps to, and applies any stored environment config from tm...

Part of the Twinmotion MCP server.

tm_render_image is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call tm_render_image to retrieve information from Twinmotion MCP without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though tm_render_image only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "tm_render_image": {}
  }
}

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These attack patterns abuse exactly the kind of access tm_render_image gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so tm_render_image only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the tm_render_image tool do? +

Render a still preview image of the model at a specified resolution by pulling the APS Model Derivative thumbnail (capped at 800x800 by the APS endpoint). Also resolves the camera_preset against model metadata to identify which 3D view it maps to, and applies any stored environment config from tm_set_environment for reference. When to use: when you need a quick visual sanity-check of an imported model (e.g. 'show me what Tower A looks like'), to preview a specific named view before committing to a full UE/Twinmotion render, or to embed a low-res preview in a chat/report. Pair with tm_list_scenes first to discover valid view names/GUIDs. When NOT to use: not for production-quality renders (APS thumbnails are low-res and raster-only; for cinematic output use Unreal Engine Movie Render Queue after FBX/USD export), not for arbitrary custom camera angles (only named views from the source file are resolvable — there is no runtime camera placement API here), not for 2D sheet exports (use tm_list_scenes to find 2D roles and fetch directly). APS scopes required: viewables:read data:read. Hits Model Derivative thumbnail + metadata endpoints only. Rate limits: APS default ~50 req/min per app per endpoint. Thumbnail endpoint is usually fast (<2s) once the model has translated; if called while status='inprogress' it returns no thumbnail. Do not loop-poll this tool — poll the manifest via tm_set_environment or tm_list_scenes instead. Errors: 401/403 = token/scope; 404 = URN not found or thumbnail not yet generated (model still translating — retry after manifest reports success); 409 = n/a; 422 = n/a; 429 = back off 30s; 5xx = APS upstream. Side effects: NONE (read-only on APS). Reads KV env_config_<urn>. Writes a row to usage_log. Idempotent.. It is categorised as a Read tool in the Twinmotion MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on tm_render_image? +

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

What risk level is tm_render_image? +

tm_render_image is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit tm_render_image? +

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

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

tm_render_image is provided by the Twinmotion MCP server (https://twinmotion-mcp.itmartin24.workers.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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