AI agents call clear_cache to permanently remove resources in Toonify — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Clearing a cache removes all stored optimization results permanently. While cache data is regenerable (making it less severe than clearing primary data), the action itself is irreversible and cannot be undone. The blast radius is medium since it only affects cached optimization results, not primary data, but an AI agent misusing this could cause performance degradation by forcing re-computation of all cached content.
From the tool's definition "Clear the optimization result cache" - clearing a cache is an irreversible deletion of stored data
Documented attack patterns abuse exactly the kind of access clear_cache gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Toonify, and nothing reaches the server without passing your rules. This is the rule we recommend for clear_cache:
{
"version": "1",
"default": "deny",
"hide": [
"clear_cache"
]
}clear_cache disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
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Clear the optimization result cache. It is categorised as a Destructive tool in the Toonify MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Toonify MCP server in PolicyLayer and add a rule for clear_cache: 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 Toonify. Nothing to install.
clear_cache is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the clear_cache 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 clear_cache. 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.
clear_cache is provided by the Toonify MCP server (pcircle-ai/toonify-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 5 Toonify tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
5 Toonify tools catalogued and risk-classified — across an index of 42,500+ MCP servers.