stream_group_create · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What stream_group_create does on Amazon SageMaker AI MCP Server

AI agents use stream_group_create 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 stream_group_create needs a policy

The tool creates a consumer group for stream processing (likely Kinesis or similar streaming service in AWS context). This is a reversible write operation—the group can be deleted or modified. It's not destructive (group can be removed), not a read operation, doesn't execute arbitrary code, and has no financial implications.

From the tool's definition Tool name 'stream_group_create' and description 'Create consumer group' indicate creation of a new resource. This is a Write operation as it creates a streaming consumer group resource that can be modified or deleted later.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

stream_group_create Rate-limited

stream_group_create 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": {
    "stream_group_create": {
      "limits": [
        {
          "counter": "stream_group_create_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 stream_group_create

What does the stream_group_create tool do? +

Create consumer group. 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 stream_group_create? +

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

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

Can I rate-limit stream_group_create? +

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

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

stream_group_create 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.