AI agents use assign_seat to create or update resources in Zola — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Zola environment.
An AI agent can call assign_seat faster than any human can review — one bad instruction and it creates or modifies resources in Zola by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Assign a guest to a specific seat in a seating chart. It is categorised as a Write tool in the Zola MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Zola MCP server in PolicyLayer and add a rule for assign_seat: 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 Zola. Nothing to install.
assign_seat 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 assign_seat 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 assign_seat. 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.
assign_seat is provided by the Zola MCP server (zola-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.