focus_view_on_point
AI agents call focus_view_on_point to retrieve information from BlenderMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The name implies a viewport navigation action (panning/zooming the view to a point), which is a non-destructive UI operation that only changes what the user sees, not the underlying scene data. This is closest to a Read/Execute action with no data modification. Classified as Read since it only adjusts the view.
From the tool's definition Tool name 'focus_view_on_point' suggests adjusting the viewport camera/view to focus on a specific point in the 3D scene.
Attacks that exploit this kind of access
focus_view_on_point. It is categorised as a Read tool in the BlenderMCP MCP Server, which means it retrieves data without modifying state.
Register the Blender MCP server in PolicyLayer and add a rule for focus_view_on_point: 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 BlenderMCP. Nothing to install.
focus_view_on_point is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the focus_view_on_point 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 focus_view_on_point. 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.
focus_view_on_point is provided by the Blender MCP server (shirshovdim/retopoflow_blender_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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