AI agents call get_job to retrieve information from Pgmcp without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves job metadata without modifying data or triggering state changes. It performs a simple query/fetch operation, consistent with Read category tools. The low severity reflects minimal risk of misuse—an AI could at worst retrieve unwanted metadata about jobs.
From the tool's definition Tool name 'get_job' and description 'Get extra information about a specific crawl job by its ID' indicate a retrieval operation with no modification or side effects.
Attacks that exploit this kind of access
Get extra information about a specific crawl job by its ID. It is categorised as a Read tool in the Pgmcp MCP Server, which means it retrieves data without modifying state.
Register the Pg MCP server in PolicyLayer and add a rule for get_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 Pgmcp. Nothing to install.
get_job 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 get_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 get_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.
get_job is provided by the Pg MCP server (veloper/pgmcp). 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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