get_experiment

THE RISK

Low Risk

Why get_experiment needs a policy

This tool retrieves and queries experiment data (variants summary, constraints) without creating, modifying, deleting, or executing any operations. The verb 'Get' and the informational nature of the output (detailed information) confirm it is a read-only operation with minimal blast radius if misused by an AI agent.

From the tool's definition Tool name 'get_experiment' and description 'Get detailed information about a specific experiment by ID' indicates data retrieval with no modification or execution of side effects.

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

POLICY

How to control get_experiment

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:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_experiment": {}
  }
}

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

Create a free account and register Iterable 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.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Iterable MCP Server tools

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All 78 Iterable MCP Server tools →

Read tools on other servers

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about get_experiment

What does the get_experiment tool do? +

Get detailed information about a specific experiment by ID, including variants summary and constraints. 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? +

Register the Iterable MCP Server MCP server in PolicyLayer and add a rule for get_experiment: 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? +

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

Can I rate-limit get_experiment? +

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

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

get_experiment 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.

CHECK YOUR STACK →