create_user · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What create_user does on Amazon SageMaker AI MCP Server

AI agents use create_user 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_user needs a policy

Creating users is a Write operation (creates new data/accounts reversibly). Severity is high because user creation can grant unauthorized access, affect billing/cost allocation, and create security management issues if misused by an AI agent without proper authorization checks. However, it is not Destructive (reversible via deletion) or Financial (no direct money movement).

From the tool's definition Tool name 'create_user' indicates creation of a new user account. While description is empty, the function name unambiguously describes a write operation that creates identity/access resources in AWS SageMaker or the broader AWS ecosystem.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_user Rate-limited

create_user 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_user": {
      "limits": [
        {
          "counter": "create_user_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_user

What does the create_user tool do? +

create_user. 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_user? +

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

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

Can I rate-limit create_user? +

Yes. Add a rate_limit block to the create_user 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_user completely? +

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

create_user 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.