This record as markdown: /tools/aiwerk-mcp-server-ghl/calendars-create-appointment.md
What calendars_create_appointment does on Ghl
AI agents use calendars_create_appointment to create or update resources in Ghl, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ghl environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
rrule | string | — | RRULE as per the iCalendar (RFC 5545) specification for recurring events. DTSTART is not required, instance ids are calculated on the basis of startTime of the |
title | string | — | Title |
address | string | — | Appointment Address |
endTime | string | — | End Time |
toNotify | boolean | — | If set to false, the automations will not run |
contactId | string | Yes | Contact Id |
startTime | string | Yes | Start Time |
calendarId | string | Yes | Calendar Id |
locationId | string | — | Location Id Defaults to GHL_LOCATION_ID when omitted. |
description | string | — | Appointment Description |
assignedUserId | string | — | Assigned User Id |
ignoreDateRange | boolean | — | If set to true, the minimum scheduling notice and date range would be ignored |
Parameters from the server's own tool schema.
Why calendars_create_appointment is rated Medium
An AI agent can call calendars_create_appointment faster than any human can review: one bad instruction and it creates or modifies resources in Ghl by the hundred, each call as confident as the last.
Risk signalsHigh parameter count (17 properties)
Attacks that exploit this kind of access
The rule that runs calendars_create_appointment safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ghl, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For calendars_create_appointment, this is the rule to start with:
calendars_create_appointment 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 Ghl, apply this rule, and every calendars_create_appointment call is checked against it from then on.
Questions about calendars_create_appointment
Create appointment. It is categorised as a Write tool in the Ghl MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
calendars_create_appointment accepts 12 parameters: rrule, title, address, endTime, toNotify, contactId, startTime, calendarId, locationId, description, assignedUserId, ignoreDateRange. Required: contactId, startTime, calendarId. The full parameter table on this page comes from the server's own tool schema.
Register the Ghl MCP server in PolicyLayer and add a rule for calendars_create_appointment: 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 Ghl. Nothing to install.
calendars_create_appointment 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 calendars_create_appointment 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 calendars_create_appointment. 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.
calendars_create_appointment is provided by the Ghl MCP server (@aiwerk/mcp-server-ghl). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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