Async job queue for long-running Blender Python scripts (renders, bakes, sims).
AI agents invoke blender_jobs to trigger actions in Blender. 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 executes arbitrary Blender Python scripts asynchronously. Running Python scripts in Blender can perform a wide range of operations including file system access, external process execution, and scene manipulation. The mention of 'renders, bakes, sims' indicates compute-intensive operations, and the ability to queue Python scripts represents significant execution power with broad blast radius if misused.
From the tool's definition Async job queue for long-running Blender Python scripts (renders, bakes, sims)
Documented attack patterns abuse exactly the kind of access blender_jobs 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_jobs:
{
"version": "1",
"default": "deny",
"tools": {
"blender_jobs": {
"limits": [
{
"counter": "blender_jobs_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}blender_jobs 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.
Free to start. No card required.
Async job queue for long-running Blender Python scripts (renders, bakes, sims). It is categorised as a Execute tool in the Blender MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Blender MCP server in PolicyLayer and add a rule for blender_jobs: 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_jobs 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 blender_jobs 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_jobs. 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_jobs 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.
Free to start. No card required.
77 Blender tools catalogued and risk-classified — across an index of 43,000+ MCP servers.