Batch image and mesh export operations.
AI agents use blender_batch to create or update resources in Blender — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Blender environment.
Export operations create new files (image and mesh formats), making this a Write operation rather than Read. The 'batch' modifier adds scale and potential for unintended bulk file creation. While not Destructive (exports don't remove source data) or Financial, exporting large batches of data could consume storage and bandwidth.
From the tool's definition Batch image and mesh export operations - exports create new files from existing Blender data without modification of the source, and can be executed at scale ('batch').
Documented attack patterns abuse exactly the kind of access blender_batch gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Blender, and nothing reaches the server without passing your rules. This is the rule we recommend for blender_batch:
{
"version": "1",
"default": "deny",
"tools": {
"blender_batch": {
"limits": [
{
"counter": "blender_batch_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}blender_batch 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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Batch image and mesh export operations. It is categorised as a Write tool in the Blender MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Blender MCP server in PolicyLayer and add a rule for blender_batch: 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 Blender. Nothing to install.
blender_batch 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 blender_batch 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 blender_batch. 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.
blender_batch is provided by the Blender MCP server (sandraschi/blender-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Blender, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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