create_role · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What create_role does on Amazon SageMaker AI MCP Server

AI agents use create_role 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_role needs a policy

Creating an IAM role modifies AWS access control configuration reversibly (roles can be deleted or modified later), making it a Write operation. High severity because role creation can expand or alter service permissions across the AWS account, potentially widening the blast radius if an agent creates overly permissive roles. Confidence is slightly reduced due to empty description, but the tool name is unambiguous.

From the tool's definition Tool name 'create_role' indicates creation of an IAM role; description is empty but the pattern of sibling tools (add_inline_policy, add_user_to_group, aggregate) suggests AWS identity/access management operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_role Rate-limited

create_role 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_role": {
      "limits": [
        {
          "counter": "create_role_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_role

What does the create_role tool do? +

create_role. 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_role? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for create_role: 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_role? +

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

Can I rate-limit create_role? +

Yes. Add a rate_limit block to the create_role 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_role completely? +

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

create_role 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.