AI agents call fetch to retrieve information from Jobs without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves a specific job record by ID from the MongoDB collection. This is a read-only operation with no side effects—it queries and returns data without creating, modifying, deleting, or executing any external operations. The narrow scope (fetching by ID) and lack of destructive capability confirm the Read category with low severity.
From the tool's definition Tool name 'fetch' and description 'Fetch a specific care job by its ID' indicate retrieval of data without modification or deletion.
Attacks that exploit this kind of access
Fetch a specific care job by its ID. It is categorised as a Read tool in the Jobs MCP Server, which means it retrieves data without modifying state.
Register the Jobs MCP server in PolicyLayer and add a rule for fetch: 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 Jobs. Nothing to install.
fetch 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 fetch 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 fetch. 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.
fetch is provided by the Jobs MCP server (xhrusvin/jobs-mcp-server). 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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