AI agents call delete_user to permanently remove resources in Amazon Location Service MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
User deletion is a destructive action that cannot be undone without restoration from backups. Even though the description is uninformative, the tool name itself clearly indicates removal of a user identity, which would eliminate access permissions, authentication credentials, and associated resources. This qualifies as Destructive rather than Write due to its irreversible nature.
From the tool's definition Tool name is 'delete_user' which indicates irreversible deletion of a user resource. The empty description prevents confirmation of scope, but the name unambiguously signals a destructive operation.
Documented attack patterns abuse exactly the kind of access delete_user gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Location Service MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_user:
{
"version": "1",
"default": "deny",
"hide": [
"delete_user"
]
}delete_user 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_user. It is categorised as a Destructive tool in the Amazon Location Service MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Amazon Location Service MCP Server MCP server in PolicyLayer and add a rule for delete_user: 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 Amazon Location Service MCP Server. Nothing to install.
delete_user 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_user 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_user. 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_user is provided by the Amazon Location Service MCP Server MCP server (awslabs.aws-location-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Amazon Location Service MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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805 Amazon Location Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.