update_resource · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What update_resource does on Amazon SageMaker AI MCP Server

AI agents use update_resource 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 update_resource needs a policy

The 'update_resource' name suggests reversible modification of AWS SageMaker resources. Without a detailed description, we cannot confirm whether it permits destructive operations, but the naming convention implies Write semantics. The confidence is moderate (0.7) due to the empty description and ambiguity about which resources can be modified and what constraints exist.

From the tool's definition Tool name is 'update_resource' with no description provided. The verb 'update' indicates modification of data rather than deletion or execution of arbitrary code.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_resource Rate-limited

update_resource 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": {
    "update_resource": {
      "limits": [
        {
          "counter": "update_resource_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 update_resource

What does the update_resource tool do? +

update_resource. 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 update_resource? +

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

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

Can I rate-limit update_resource? +

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

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

update_resource 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.