AI agents use smooth_model to create or update resources in Metashape MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Metashape MCP Server environment.
Based on the name alone, 'smooth_model' likely applies a smoothing operation to a 3D model geometry within Metashape, which would be a reversible modification (Write). However, since the description is empty, confidence is low. It could also be considered Execute if it triggers a processing pipeline.
From the tool's definition Tool name 'smooth_model' — description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access smooth_model gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Metashape MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for smooth_model:
{
"version": "1",
"default": "deny",
"tools": {
"smooth_model": {
"limits": [
{
"counter": "smooth_model_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}smooth_model 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.
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smooth_model. It is categorised as a Write tool in the Metashape MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Metashape MCP Server MCP server in PolicyLayer and add a rule for smooth_model: 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 Metashape MCP Server. Nothing to install.
smooth_model is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the smooth_model 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.
Set action: deny in the PolicyLayer policy for smooth_model. 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.
smooth_model is provided by the Metashape MCP Server MCP server (jenkinsm13/metashape-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Metashape MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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112 Metashape MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.