start_batch_translation · Amazon SageMaker AI MCP Server MCP

WHAT IT DOES

What start_batch_translation does on Amazon SageMaker AI MCP Server

AI agents invoke start_batch_translation to trigger actions in Amazon SageMaker AI MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

THE RISK

High Risk

Why start_batch_translation needs a policy

Batch translation jobs execute code/models in SageMaker and produce outputs whose nature and scope depend on arguments provided. This is an Execute action rather than Read (no data retrieval), Write (not merely creating reversible records), or Destructive (translation outputs are not inherently irreversible).

From the tool's definition Tool name 'start_batch_translation' indicates initiating a translation job; AWS SageMaker batch operations trigger external ML processing with resource consumption and runtime effects that depend on input parameters (data source, model selection,…

Documented attack patterns abuse exactly the kind of access start_batch_translation gives an agent:

POLICY

How to control start_batch_translation

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon SageMaker AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for start_batch_translation:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "start_batch_translation": {
      "limits": [
        {
          "counter": "start_batch_translation_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

start_batch_translation stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register Amazon SageMaker AI MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Amazon SageMaker AI MCP Server tools

Destructive bulk_delete_by_criteria bulk_delete_by_criteria Destructive cache_delete Delete a value from the cache. Destructive cache_delete_many Delete multiple values from the cache. Destructive cache_delete_multi Delete multiple values from the cache (alias for delete_many). Destructive cancel_logs_insight_query cancel_logs_insight_query Destructive CancelAHORunBatch CancelAHORunBatch Destructive delete delete Destructive delete_access_key delete_access_key

All 805 Amazon SageMaker AI MCP Server tools →

Execute tools on other servers

Android Forensics ADB MCP Server adb_shell_command EMBA-MCP run_emba_scan Frida Game Hacking MCP remove_breakpoint Procmon request_elevation

Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
High-risk tools in Amazon SageMaker AI MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about start_batch_translation

What does the start_batch_translation tool do? +

start_batch_translation. It is categorised as a Execute tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on start_batch_translation? +

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

start_batch_translation is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit start_batch_translation? +

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

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

start_batch_translation 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.

Enforce policy on every Amazon SageMaker AI MCP Server tool call.

Start from Amazon SageMaker AI MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →

Free to start. No card required.

805 Amazon SageMaker AI MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.