Remesh an existing 3D model or convert it to different formats using Meshy AI. Use this to optimize polygon count, change topology, convert formats, or reposition model origin. Args: - input_task_id (string, optional): Task ID of an existing completed task to remesh - model_url (string, optional)...
AI agents invoke meshy_remesh to trigger actions in Meshy 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.
This tool initiates an external computation job (remeshing/format conversion) on Meshy's platform. It doesn't merely read data, nor does it irreversibly delete anything — it creates a new processed version of a model. Since it triggers an external operation whose effects depend on arguments (target formats, topology changes, polygon optimization), Execute is the most appropriate category.
From the tool's definition 'Remesh an existing 3D model or convert it to different formats using Meshy AI' — triggers an external AI processing operation that transforms/modifies a 3D model
Documented attack patterns abuse exactly the kind of access meshy_remesh gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Meshy MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for meshy_remesh:
{
"version": "1",
"default": "deny",
"tools": {
"meshy_remesh": {
"limits": [
{
"counter": "meshy_remesh_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}meshy_remesh 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.
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Remesh an existing 3D model or convert it to different formats using Meshy AI. Use this to optimize polygon count, change topology, convert formats, or reposition model origin. Args: - input_task_id (string, optional): Task ID of an existing completed task to remesh - model_url (string, optional): Direct URL to a model file to remesh (Provide either input_task_id or model_url) - target_formats (array, optional): Output formats to generate (default: [. It is categorised as a Execute tool in the Meshy MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Meshy MCP Server MCP server in PolicyLayer and add a rule for meshy_remesh: 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 Meshy MCP Server. Nothing to install.
meshy_remesh is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the meshy_remesh 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 meshy_remesh. 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.
meshy_remesh is provided by the Meshy MCP Server MCP server (meshy-dev/meshy-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Meshy MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
20 Meshy MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.