mark_no_show

Mark a booking as no-show when the customer did not attend.

SERVERFavCRM SOURCEhttps://api.favcrm.io/mcp

Medium RISK CLASS

Category Write

Parameters 11 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-favcrm-favcrm/mark-no-show.md

WHAT IT DOES

What mark_no_show does on FavCRM

AI agents use mark_no_show 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 mark as no-show

Parameters from the server's own tool schema.

RISK

Why mark_no_show is rated Medium

The tool updates the status of a booking to 'no-show', which is a write operation that changes data state. It's not destructive (booking isn't deleted), not financial (no money moved), and not execute (no arbitrary code/commands). The severity is medium because incorrectly marking bookings as no-show could impact business operations, customer service records, and staff scheduling, but can typically be corrected.

From the tool's definition Tool description states 'Mark a booking as no-show' — a state change operation that modifies an existing booking record. This is reversible modification of data, not deletion or destruction.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs mark_no_show 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 mark_no_show, this is the rule to start with:

mark_no_show Rate-limited

mark_no_show 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "mark_no_show": {
      "limits": [
        {
          "counter": "mark_no_show_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect FavCRM, apply this rule, and every mark_no_show call is checked against it from then on.

FAQ

Questions about mark_no_show

What does the mark_no_show tool do? +

Mark a booking as no-show when the customer did not attend. 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.

What parameters does mark_no_show accept? +

mark_no_show accepts 1 parameter: bookingId. Required: bookingId. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on mark_no_show? +

Register the FavCRM MCP server in PolicyLayer and add a rule for mark_no_show: 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.

What risk level is mark_no_show? +

mark_no_show is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit mark_no_show? +

Yes. Add a rate_limit block to the mark_no_show 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.

How do I block mark_no_show completely? +

Set action: deny in the PolicyLayer policy for mark_no_show. 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.

What MCP server provides mark_no_show? +

mark_no_show 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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