delete_study

THE RISK

Critical Risk

Why delete_study needs a policy

The tool name explicitly indicates deletion ('delete_study'). Deletion is an irreversible operation that cannot be undone. While confidence is slightly reduced due to lack of a description confirming the scope and nature of the study resource being deleted, the verb 'delete' itself is unambiguous enough to classify this as Destructive.

From the tool's definition Tool name is 'delete_study' which contains the verb 'delete' indicating irreversible data removal. No description provided, but the semantic meaning of 'delete' combined with AWS context suggests permanent deletion of a study resource.

Documented attack patterns abuse exactly the kind of access delete_study gives an agent:

POLICY

How to control delete_study

PolicyLayer is an MCP gateway — it sits between your AI agents and AWS, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_study:

policy.json

{
  "version": "1",
  "default": "deny",
  "hide": [
    "delete_study"
  ]
}

delete_study disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.

Create a free account and register AWS — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RESTRICT THIS TOOL →

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EXPLORE

Related tools and policies

More AWS tools

Destructive bulk_delete_by_criteria bulk_delete_by_criteria Destructive cache_delete Delete a value from the cache. Args: key: The key to delete Returns: Destructive cache_delete_many Delete multiple values from the cache. Args: keys: List of keys to delete Destructive cache_delete_multi Delete multiple values from the cache (alias for delete_many). Args: keys: Li Destructive delete Delete a Valkey key. Args: key (str): The key to delete. Returns: Destructive delete_access_key delete_access_key Destructive delete_datastore Delete a data store from AWS HealthImaging. Destructive delete_group delete_group

All 300 AWS tools →

Destructive tools on other servers

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Go deeper

Govern infrastructure agents → Production lockdown, region locks, and approval-to-delete on every infrastructure call agents make.
Critical-risk tools in AWS → Every critical-risk tool this server exposes, in one view.
All critical-risk MCP tools → Every critical-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Blast radius → How much damage one compromised or confused agent can do — and how to bound it.
Tool call approval → Approval gates on individual tool calls: auto-allow, prompt, or deny.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about delete_study

What does the delete_study tool do? +

delete_study. It is categorised as a Destructive tool in the AWS MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on delete_study? +

Register the AWS MCP server in PolicyLayer and add a rule for delete_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. Nothing to install.

What risk level is delete_study? +

delete_study is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit delete_study? +

Yes. Add a rate_limit block to the delete_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.

How do I block delete_study completely? +

Set action: deny in the PolicyLayer policy for delete_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.

What MCP server provides delete_study? +

delete_study is provided by the AWS MCP server (@awslabs/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AWS tool call.

Start from AWS, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →