Check the progress of an interactive login started with booking_login. Returns status
AI agents call booking_login_status to retrieve information from MCP Booking without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves the current status of a login session. It has no side effects, does not modify any data, and does not initiate any action. It is a pure read/query operation.
From the tool's definition Check the progress of an interactive login started with booking_login. Returns status
Attacks that exploit this kind of access
Check the progress of an interactive login started with booking_login. Returns status. It is categorised as a Read tool in the MCP Booking MCP Server, which means it retrieves data without modifying state.
Register the MCP Booking MCP server in PolicyLayer and add a rule for booking_login_status: 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 MCP Booking. Nothing to install.
booking_login_status 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 booking_login_status 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 booking_login_status. 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.
booking_login_status is provided by the MCP Booking MCP server (markswendsen-code/mcp-booking). 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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