AI agents invoke image_to_3d_model to trigger actions in Blender MCP Bridge. 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.
The server description explicitly mentions generating 3D models from images as a core capability, implying this tool triggers external operations (likely executing scripts/processes within Blender to process an image and create geometry). This falls under Execute since it runs operations within Blender's environment.
From the tool's definition Tool name 'image_to_3d_model' on a server that 'execute Python scripts' and 'generate 3D models from images' in Blender's internal environment
Documented attack patterns abuse exactly the kind of access image_to_3d_model gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Blender MCP Bridge, and nothing reaches the server without passing your rules. This is the rule we recommend for image_to_3d_model:
{
"version": "1",
"default": "deny",
"tools": {
"image_to_3d_model": {
"limits": [
{
"counter": "image_to_3d_model_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}image_to_3d_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.
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image_to_3d_model. It is categorised as a Execute tool in the Blender MCP Bridge MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Blender MCP Bridge MCP server in PolicyLayer and add a rule for image_to_3d_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 Blender MCP Bridge. Nothing to install.
image_to_3d_model 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 image_to_3d_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.
Set action: deny in the PolicyLayer policy for image_to_3d_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.
image_to_3d_model is provided by the Blender MCP Bridge MCP server (mithran-balachander/blender-mcp-antigravity). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Blender MCP Bridge, 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.
3 Blender MCP Bridge tools catalogued and risk-classified — across an index of 43,000+ MCP servers.