memory_batch_create_records

WHAT IT DOES

What memory_batch_create_records does on Amazon SageMaker AI MCP Server

AI agents use memory_batch_create_records 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 memory_batch_create_records needs a policy

This tool creates or adds records in batch, which is a Write operation—it modifies data reversibly. Within the SageMaker context, batch record creation could affect training datasets, metadata, or experiment tracking. The batch nature amplifies the scope of modification. High severity reflects potential impact on multiple records at once, though without destructive capability.

From the tool's definition Tool name 'memory_batch_create_records' indicates batch creation of records. The 'create' action modifies data by adding new records. Description is empty, which reduces confidence but does not change the fundamental action category.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

memory_batch_create_records Rate-limited

memory_batch_create_records 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": {
    "memory_batch_create_records": {
      "limits": [
        {
          "counter": "memory_batch_create_records_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 memory_batch_create_records

What does the memory_batch_create_records tool do? +

memory_batch_create_records. 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 memory_batch_create_records? +

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

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

Can I rate-limit memory_batch_create_records? +

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

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

memory_batch_create_records 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.