AI agents call delete_agent_runtime to permanently remove resources in Amazon SageMaker AI MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The 'delete' verb typically indicates a Destructive action that cannot be undone. In the context of SageMaker agents, deleting an agent runtime would remove configured infrastructure or execution environment. Even without explicit description, the semantics of 'delete' applied to a 'runtime' resource places this in the Destructive category.
From the tool's definition Tool name 'delete_agent_runtime' contains 'delete', indicating irreversible removal of a runtime agent in SageMaker. Description is empty, limiting confirmation, but the 'delete' verb strongly suggests data or resource destruction.
Documented attack patterns abuse exactly the kind of access delete_agent_runtime gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon SageMaker AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_agent_runtime:
{
"version": "1",
"default": "deny",
"hide": [
"delete_agent_runtime"
]
}delete_agent_runtime 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_agent_runtime. It is categorised as a Destructive tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for delete_agent_runtime: 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 SageMaker AI MCP Server. Nothing to install.
delete_agent_runtime 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_agent_runtime 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_agent_runtime. 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_agent_runtime is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Amazon SageMaker AI 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 Amazon SageMaker AI MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.