delete_instance_in_study
AI agents call delete_instance_in_study to permanently remove resources in Amazon ElastiCache Memcached MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Even though the description is uninformative, the verb 'delete' combined with 'instance' indicates this tool removes data permanently. In an ElastiCache Memcached context, deleting an instance destroys that resource and any associated data. This is an irreversible action with no undo capability, placing it in the Destructive category.
From the tool's definition Tool name 'delete_instance_in_study' indicates irreversible deletion of a study instance. The description is empty, but the name alone strongly suggests a destructive operation that cannot be undone.
Attacks that exploit this kind of access
delete_instance_in_study. It is categorised as a Destructive tool in the Amazon ElastiCache Memcached MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Amazon ElastiCache Memcached MCP Server MCP server in PolicyLayer and add a rule for delete_instance_in_study: 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 ElastiCache Memcached MCP Server. Nothing to install.
delete_instance_in_study 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_instance_in_study 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_instance_in_study. 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_instance_in_study is provided by the Amazon ElastiCache Memcached MCP Server MCP server (awslabs.memcached-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.