create_support_case · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What create_support_case does on Amazon SageMaker AI MCP Server

AI agents use create_support_case to create or update resources in Amazon SageMaker AI MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Amazon SageMaker AI MCP Server environment.

WHY IT NEEDS A POLICY

Why create_support_case needs a policy

Creating a support case writes new data (case record) to AWS support systems. This is reversible (cases can be closed or deleted) and has no immediate financial or destructive impact, though it may incur support costs depending on AWS plan terms. Without description details, confidence is moderate. Categorized as Write rather than Financial because the primary function is data creation, not direct money movement.

From the tool's definition Tool name 'create_support_case' indicates creation of a support case, a reversible data modification action. Description is empty, reducing confidence.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_support_case Rate-limited

create_support_case stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_support_case": {
      "limits": [
        {
          "counter": "create_support_case_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Amazon SageMaker AI MCP Server, so you can run agents against it safely.

FAQ

Questions about create_support_case

What does the create_support_case tool do? +

create_support_case. It is categorised as a Write tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_support_case? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for create_support_case: 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.

What risk level is create_support_case? +

create_support_case is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_support_case? +

Yes. Add a rate_limit block to the create_support_case 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 create_support_case completely? +

Set action: deny in the PolicyLayer policy for create_support_case. 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 create_support_case? +

create_support_case 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.