slice_model · OrcaSlicer MCP Server MCP: Risk & Policy

WHAT IT DOES

What slice_model does on OrcaSlicer MCP Server

AI agents invoke slice_model to trigger actions in OrcaSlicer MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why slice_model needs a policy

This tool invokes an external CLI command, making it an Execute category tool. Severity is high because: (1) it runs an external process that could potentially be exploited via path traversal or command injection if inputs aren't sanitized, (2) it writes output files to the filesystem which could overwrite existing files, and (3) an agent with poor prompt-following could slice incorrect models or write to unintended…

From the tool's definition Tool description states it will 'Run OrcaSlicer CLI to slice a model file' — executing an external command/process with user-supplied arguments (input/output filenames, profiles).

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

slice_model Rate-limited

slice_model stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "slice_model": {
      "limits": [
        {
          "counter": "slice_model_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches OrcaSlicer MCP Server, so you can run agents against it safely.

FAQ

Questions about slice_model

What does the slice_model tool do? +

Run OrcaSlicer CLI to slice a model file. Specify input/output filenames and optionally profiles to use. It is categorised as a Execute tool in the OrcaSlicer MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on slice_model? +

Register the OrcaSlicer MCP Server MCP server in PolicyLayer and add a rule for slice_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 OrcaSlicer MCP Server. Nothing to install.

What risk level is slice_model? +

slice_model is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit slice_model? +

Yes. Add a rate_limit block to the slice_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.

How do I block slice_model completely? +

Set action: deny in the PolicyLayer policy for slice_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.

What MCP server provides slice_model? +

slice_model is provided by the OrcaSlicer MCP Server MCP server (itsumonotakumi/orcaslicer-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.