Low Risk

get_experiment_metrics

Get experiment metrics for A/B testing analysis (currently supports email experiments only)

How to control get_experiment_metrics ↓

What get_experiment_metrics does on Iterable MCP Server

AI agents call get_experiment_metrics to retrieve information from Iterable MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why get_experiment_metrics needs a policy

This tool retrieves and queries experiment metrics data from the Iterable platform for analysis purposes. It performs no data modification, deletion, code execution, or financial operations. The blast radius of misuse is minimal—an agent could only access or exfiltrate existing A/B test metrics, not modify campaigns or user data.

From the tool's definition Tool name 'get_experiment_metrics' and description 'Get experiment metrics for A/B testing analysis' indicate a retrieval operation with no modification or side effects.

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

How to control get_experiment_metrics

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_experiment_metrics": {}
  }
}

get_experiment_metrics is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Iterable MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about get_experiment_metrics

What does the get_experiment_metrics tool do? +

Get experiment metrics for A/B testing analysis (currently supports email experiments only). It is categorised as a Read tool in the Iterable MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_experiment_metrics? +

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

What risk level is get_experiment_metrics? +

get_experiment_metrics is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_experiment_metrics? +

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

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

get_experiment_metrics is provided by the Iterable MCP Server MCP server (iterable/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 Iterable MCP Server tool call.

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

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78 Iterable MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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