AI agents call check_inbox to retrieve information from Mail without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only reads and retrieves email metadata and summaries from the inbox without creating, modifying, deleting, or executing any operations. It is a straightforward data query operation that poses minimal risk even if misused by an AI agent, as the worst outcome would be information disclosure of already-accessible email content.
From the tool's definition Tool description states 'unread count + last N message summaries' — purely retrieval and querying operations with no modifications or side effects.
Attacks that exploit this kind of access
Quick inbox check: unread count + last N message summaries. It is categorised as a Read tool in the Mail MCP Server, which means it retrieves data without modifying state.
Register the Mail MCP server in PolicyLayer and add a rule for check_inbox: 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 Mail. Nothing to install.
check_inbox 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 check_inbox 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 check_inbox. 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.
check_inbox is provided by the Mail MCP server (kpihx/mail-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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