List experiments with optional filtering by campaign, status, and date range. Supports pagination.
AI agents call list_experiments 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.
This tool performs a read-only operation that retrieves experiment data from the Iterable platform. It allows filtering and pagination of results but does not create, modify, delete, or execute any operations. The severity is low because listing/querying data poses minimal risk even if misused by an AI agent—the worst outcome would be accessing metadata about experiments the agent is already authorized to view.
From the tool's definition Tool name 'list_experiments' and description 'List experiments with optional filtering by campaign, status, and date range. Supports pagination.' indicate retrieval and querying of existing experiment data without modification or side effects.
Documented attack patterns abuse exactly the kind of access list_experiments gives an agent:
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 list_experiments:
{
"version": "1",
"default": "deny",
"tools": {
"list_experiments": {}
}
}list_experiments is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List experiments with optional filtering by campaign, status, and date range. Supports pagination. It is categorised as a Read tool in the Iterable MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Iterable MCP Server MCP server in PolicyLayer and add a rule for list_experiments: 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.
list_experiments is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_experiments 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.
Set action: deny in the PolicyLayer policy for list_experiments. 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.
list_experiments 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.
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.
Free to start. No card required.
78 Iterable MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.