This record as markdown: /tools/io-favcrm-favcrm/confirm-booking.md
What confirm_booking does on FavCRM
AI agents use confirm_booking to create or update resources in FavCRM, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FavCRM environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
bookingId | string | Yes | The booking ID to confirm |
Parameters from the server's own tool schema.
Why confirm_booking is rated Medium
This tool modifies booking data reversibly—confirming a booking changes its state but can be undone by canceling or modifying the booking later. It does not delete data (Destructive), execute arbitrary code (Execute), involve financial transactions (Financial), or merely retrieve information (Read).
From the tool's definition Tool name 'confirm_booking' and description 'Confirm a pending booking' indicate state modification of an existing booking record from pending to confirmed status.
Attacks that exploit this kind of access
The rule that runs confirm_booking safely
PolicyLayer is an MCP gateway: it sits between your AI agents and FavCRM, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For confirm_booking, this is the rule to start with:
confirm_booking stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect FavCRM, apply this rule, and every confirm_booking call is checked against it from then on.
Questions about confirm_booking
Confirm a pending booking. It is categorised as a Write tool in the FavCRM MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
confirm_booking accepts 1 parameter: bookingId. Required: bookingId. The full parameter table on this page comes from the server's own tool schema.
Register the FavCRM MCP server in PolicyLayer and add a rule for confirm_booking: 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 FavCRM. Nothing to install.
confirm_booking is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the confirm_booking 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 confirm_booking. 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.
confirm_booking is provided by the FavCRM MCP server (https://api.favcrm.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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