Generate a Blender Python script from a natural language prompt using a local LLM (Ollama).
AI agents invoke generate_blender_script 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 generates and likely executes arbitrary Python scripts in Blender based on natural language input. Even if it only generates (not executes) scripts, the downstream intent is execution of code whose effects are entirely determined by the LLM output and user prompt, making it an Execute-category tool.
From the tool's definition Generate a Blender Python script from a natural language prompt... using a local LLM (Ollama)
Documented attack patterns abuse exactly the kind of access generate_blender_script 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 generate_blender_script:
{
"version": "1",
"default": "deny",
"tools": {
"generate_blender_script": {
"limits": [
{
"counter": "generate_blender_script_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}generate_blender_script 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.
Generate a Blender Python script from a natural language prompt using a local LLM (Ollama). 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 generate_blender_script: 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.
generate_blender_script 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 generate_blender_script 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 generate_blender_script. 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.
generate_blender_script 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.