AI agents call list_jobs to retrieve information from Extracto without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns a list of past async jobs with no side effects, altering state, or executing operations. It is a straightforward retrieval operation with minimal risk even if invoked unexpectedly by an AI agent.
From the tool's definition Tool name 'list_jobs' and description 'List your recent async extraction jobs, newest first' indicate a read-only operation that retrieves historical job metadata without modifying or deleting data.
Attacks that exploit this kind of access
List your recent async extraction jobs, newest first. It is categorised as a Read tool in the Extracto MCP Server, which means it retrieves data without modifying state.
Register the Extracto MCP server in PolicyLayer and add a rule for list_jobs: 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 Extracto. Nothing to install.
list_jobs 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_jobs 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_jobs. 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_jobs is provided by the Extracto MCP server (massanaroger/extracto-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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