AI agents call delete_instance_in_study to permanently remove resources in AWS AppSync MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The 'delete' verb indicates this tool performs an irreversible deletion of an instance (likely a data record or resource) within a study context. Even though the description is empty, the name itself strongly suggests a destructive action that cannot be undone. Classified as Destructive rather than Write because deletion is inherently irreversible.
From the tool's definition Tool name 'delete_instance_in_study' uses the verb 'delete', which is typically an irreversible operation. The context of AWS services and the sibling tools suggest this operates on data structures within AppSync or related AWS services.
Documented attack patterns abuse exactly the kind of access delete_instance_in_study gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS AppSync MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_instance_in_study:
{
"version": "1",
"default": "deny",
"hide": [
"delete_instance_in_study"
]
} delete_instance_in_study 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_instance_in_study. It is categorised as a Destructive tool in the AWS AppSync MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the AWS AppSync 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 AWS AppSync 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 AWS AppSync MCP Server MCP server (awslabs.aws-appsync-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS AppSync 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 AppSync MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.