start_batch_analysis

THE RISK

High Risk

Why start_batch_analysis needs a policy

This tool initiates a batch analysis job on an external service (Azure OpenAI), which is a triggered operation that executes code/processes outside the local system. While not destructive or financial in nature, it represents code execution and consumes external resources.

From the tool's definition Tool name 'start_batch_analysis' and description 'Start a batch analysis job using Azure OpenAI' indicate triggering an external operation (Azure OpenAI batch job execution) whose effects depend on arguments provided by the caller.

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

POLICY

How to control start_batch_analysis

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

policy.json

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

start_batch_analysis 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 Smartsheet 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

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All 34 Smartsheet MCP Server tools →

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Go deeper

High-risk tools in Smartsheet 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 →

FAQ

Questions about start_batch_analysis

What does the start_batch_analysis tool do? +

Start a batch analysis job using Azure OpenAI. It is categorised as a Execute tool in the Smartsheet 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_analysis? +

Register the Smartsheet MCP Server MCP server in PolicyLayer and add a rule for start_batch_analysis: 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 Smartsheet MCP Server. Nothing to install.

What risk level is start_batch_analysis? +

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

Can I rate-limit start_batch_analysis? +

Yes. Add a rate_limit block to the start_batch_analysis 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_analysis completely? +

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

start_batch_analysis is provided by the Smartsheet MCP Server MCP server (terilios/smartsheet-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Smartsheet MCP Server tool call.

Start from Smartsheet 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 →