Delete a value from the cache.
AI agents call cache_delete to permanently remove resources in AWS Labs CloudTrail MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Cache deletion is an irreversible operation that removes data. Although the blast radius is limited to cached values rather than permanent data stores, deletion operations are inherently destructive. If an AI agent mistakenly deletes critical cache entries, it could cause service degradation, lost session data, or temporary system failures.
From the tool's definition Tool name is 'cache_delete' with description 'Delete a value from the cache.' The verb 'Delete' combined with the irreversible nature of cache deletion (data removal without undo capability) fits the Destructive category.
Documented attack patterns abuse exactly the kind of access cache_delete gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Labs CloudTrail MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for cache_delete:
{
"version": "1",
"default": "deny",
"hide": [
"cache_delete"
]
}cache_delete 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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Delete a value from the cache. It is categorised as a Destructive tool in the AWS Labs CloudTrail MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the AWS Labs CloudTrail MCP Server MCP server in PolicyLayer and add a rule for cache_delete: 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 AWS Labs CloudTrail MCP Server. Nothing to install.
cache_delete 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 cache_delete 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 cache_delete. 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.
cache_delete is provided by the AWS Labs CloudTrail MCP Server MCP server (awslabs.cloudtrail-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS Labs CloudTrail MCP Server, 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.
805 AWS Labs CloudTrail MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.