delete_instance_in_study

THE RISK

Critical Risk

Why delete_instance_in_study needs a policy

Tools that delete data are irreversible and cannot be undone, placing them in the Destructive category. Even without a detailed description, the explicit use of 'delete' in the tool name is a clear indicator. Given the AWS context (likely data processing or medical data via AWS HealthLake or similar service), deleting an instance would constitute loss of data.

From the tool's definition Tool name 'delete_instance_in_study' contains the verb 'delete', which indicates irreversible removal of data. The description is empty, but the name alone strongly suggests a destructive operation.

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

POLICY

How to control delete_instance_in_study

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

policy.json

{
  "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.

Create a free account and register Amazon Data Processing MCP Server — 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 →

Free to start. No card required.

EXPLORE

Related tools and policies

More Amazon Data Processing MCP Server tools

Destructive bulk_delete_by_criteria bulk_delete_by_criteria Destructive cache_delete Delete a value from the cache. Destructive cache_delete_many Delete multiple values from the cache. Destructive cache_delete_multi Delete multiple values from the cache (alias for delete_many). Destructive cancel_logs_insight_query cancel_logs_insight_query Destructive CancelAHORunBatch CancelAHORunBatch Destructive delete delete Destructive delete_access_key delete_access_key

All 805 Amazon Data Processing MCP Server tools →

Destructive tools on other servers

Android Forensics ADB MCP Server create_full_backup 0xarchive web3_revoke_key Frida Game Hacking MCP clear_scan cPanel MCP Server clear_spam_box

Go deeper

Critical-risk tools in Amazon Data Processing MCP Server → 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 →

FAQ

Questions about delete_instance_in_study

What does the delete_instance_in_study tool do? +

delete_instance_in_study. It is categorised as a Destructive tool in the Amazon Data Processing MCP Server 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_instance_in_study? +

Register the Amazon Data Processing 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 Data Processing MCP Server. Nothing to install.

What risk level is delete_instance_in_study? +

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.

Can I rate-limit delete_instance_in_study? +

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.

How do I block delete_instance_in_study completely? +

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.

What MCP server provides delete_instance_in_study? +

delete_instance_in_study is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Amazon Data Processing MCP Server tool call.

Start from Amazon Data Processing MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →