resolve_support_case · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What resolve_support_case does on Amazon SageMaker AI MCP Server

AI agents use resolve_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 resolve_support_case needs a policy

The tool appears to update support case data (marking as resolved), which is a reversible modification. Without a detailed description, confidence is moderate. This is categorized as Write rather than Execute because it modifies structured data state rather than running arbitrary code, though the exact impact depends on what 'resolve' entails in AWS Support.

From the tool's definition Tool name 'resolve_support_case' indicates modification of a support case's state/status. While the description is empty, the verb 'resolve' in context of support operations typically means updating or closing a case, which is a reversible write operation.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

resolve_support_case Rate-limited

resolve_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": {
    "resolve_support_case": {
      "limits": [
        {
          "counter": "resolve_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 resolve_support_case

What does the resolve_support_case tool do? +

resolve_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 resolve_support_case? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for resolve_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 resolve_support_case? +

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

Can I rate-limit resolve_support_case? +

Yes. Add a rate_limit block to the resolve_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 resolve_support_case completely? +

Set action: deny in the PolicyLayer policy for resolve_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 resolve_support_case? +

resolve_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.