calendars_update_schedule

Update user availability schedule

SERVERGhl SOURCE@aiwerk/mcp-server-ghl

Medium RISK CLASS

Category Write

Parameters 41 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/aiwerk-mcp-server-ghl/calendars-update-schedule.md

WHAT IT DOES

What calendars_update_schedule does on Ghl

AI agents use calendars_update_schedule 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
`id`	string	Yes	Unique identifier of the schedule to update
`name`	string	—	Human-readable name for the schedule
`rules`	array	—	Updated schedule rules defining when the schedule is active
`timezone`	string	—	Updated timezone for the schedule (IANA timezone identifier)

Parameters from the server's own tool schema.

RISK

Why calendars_update_schedule is rated Medium

An AI agent can call calendars_update_schedule 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.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

calendars_update_schedule Rate-limited

calendars_update_schedule 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": {
    "calendars_update_schedule": {
      "limits": [
        {
          "counter": "calendars_update_schedule_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 Ghl, apply this rule, and every calendars_update_schedule call is checked against it from then on.

FAQ

Questions about calendars_update_schedule

What does the calendars_update_schedule tool do? +

Update user availability schedule. 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.

What parameters does calendars_update_schedule accept? +

calendars_update_schedule accepts 4 parameters: id, name, rules, timezone. Required: id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on calendars_update_schedule? +

Register the Ghl MCP server in PolicyLayer and add a rule for calendars_update_schedule: 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.

What risk level is calendars_update_schedule? +

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

Can I rate-limit calendars_update_schedule? +

Yes. Add a rate_limit block to the calendars_update_schedule 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 calendars_update_schedule completely? +

Set action: deny in the PolicyLayer policy for calendars_update_schedule. 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 calendars_update_schedule? +

calendars_update_schedule 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.

KEEP EXPLORING

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Guides

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