Start a data export job that processes as a background job. Use
AI agents invoke start_export_job to trigger actions in Iterable 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.
Although the tool is non-destructive and retrieves data rather than modifying it directly, it crosses the threshold into Execute because it triggers and manages a background job—an operation whose effects are externally managed and depend on the arguments provided (export scope, filters, destination).
From the tool's definition The tool description states 'Start a data export job that processes as a background job.' This initiates an external operation (background job processing) whose side effects depend on export parameters (what data is exported, scope, destination).
Documented attack patterns abuse exactly the kind of access start_export_job 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 start_export_job:
{
"version": "1",
"default": "deny",
"tools": {
"start_export_job": {
"limits": [
{
"counter": "start_export_job_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}start_export_job 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.
Free to start. No card required.
Start a data export job that processes as a background job. Use. It is categorised as a Execute tool in the Iterable MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Iterable MCP Server MCP server in PolicyLayer and add a rule for start_export_job: 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.
start_export_job is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the start_export_job 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 start_export_job. 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.
start_export_job 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.