cache_append · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What cache_append does on Amazon SageMaker AI MCP Server

AI agents use cache_append 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 cache_append needs a policy

The tool modifies existing data by appending content to it, which is a reversible write operation. It does not delete or execute code. Confidence is moderate because the description is minimal and the server context (SageMaker AI MCP) doesn't fully clarify what cache/store is being modified, but appending to a value is canonically a Write operation.

From the tool's definition Append a string to an existing value

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

cache_append Rate-limited

cache_append 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": {
    "cache_append": {
      "limits": [
        {
          "counter": "cache_append_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 cache_append

What does the cache_append tool do? +

Append a string to an existing value. 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 cache_append? +

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

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

Can I rate-limit cache_append? +

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

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

cache_append 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.