create_api_cache · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What create_api_cache does on Amazon SageMaker AI MCP Server

AI agents use create_api_cache 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_api_cache needs a policy

The tool creates (not reads or deletes) a caching infrastructure component, which is a reversible write operation. Without a description, confidence is reduced, but the 'create_' prefix strongly suggests Write category. Severity is medium because misconfiguring cache creation could affect API performance and data consistency, but typically does not cause financial loss or irreversible destruction.

From the tool's definition Tool name 'create_api_cache' indicates creation of a cache resource. Description is empty, limiting evidence specificity.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_api_cache Rate-limited

create_api_cache 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_api_cache": {
      "limits": [
        {
          "counter": "create_api_cache_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_api_cache

What does the create_api_cache tool do? +

create_api_cache. 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_api_cache? +

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

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

Can I rate-limit create_api_cache? +

Yes. Add a rate_limit block to the create_api_cache 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_api_cache completely? +

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

create_api_cache 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.