AI agents call delete_schedule to permanently remove resources in AWS Labs amazon-keyspaces MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The delete_schedule tool performs an irreversible deletion operation on a schedule object within Amazon Keyspaces/Cassandra. Deletion operations cannot be undone and result in permanent loss of the schedule configuration. While the description is empty (lowering confidence slightly), the tool name itself is unambiguous.
From the tool's definition Tool name is 'delete_schedule' which directly indicates deletion of a schedule resource. The verb 'delete' is characteristic of destructive operations that irreversibly remove data or configurations.
Documented attack patterns abuse exactly the kind of access delete_schedule gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Labs amazon-keyspaces MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_schedule:
{
"version": "1",
"default": "deny",
"hide": [
"delete_schedule"
]
} delete_schedule 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_schedule. It is categorised as a Destructive tool in the AWS Labs amazon-keyspaces MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the AWS Labs amazon-keyspaces MCP Server MCP server in PolicyLayer and add a rule for delete_schedule: 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 amazon-keyspaces MCP Server. Nothing to install.
delete_schedule 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 delete_schedule 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 delete_schedule. 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.
delete_schedule is provided by the AWS Labs amazon-keyspaces MCP Server MCP server (awslabs.amazon-keyspaces-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 amazon-keyspaces 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 amazon-keyspaces MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.