calendar_update_event
Update an existing event in Google Calendar. Can modify title, time, location, description, and attendees. Only specified fields will be updated.
This record as markdown: /tools/io-github-saloprj-dialogbrain/calendar-update-event.md
What calendar_update_event does on Dialogbrain
AI agents use calendar_update_event to create or update resources in Dialogbrain, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dialogbrain environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
end | string | — | New end time in ISO 8601 format. Optional. |
start | string | — | New start time in ISO 8601 format. Optional. |
summary | string | — | New event title/summary. Optional. |
event_id | string | Yes | ID of the event to update. Required. |
location | string | — | New event location. Optional. |
attendees | array | — | New list of attendee emails. Replaces existing attendees. |
calendar_id | string | — | Calendar ID containing the event. Defaults to primary. |
description | string | — | New event description. Optional. |
Parameters from the server's own tool schema.
Why calendar_update_event is rated Medium
This tool modifies existing calendar events but does not delete or destroy data, making it Write rather than Destructive. The severity is medium because misuse could cause scheduling confusion, missed meetings, or unintended attendee changes, but effects are reversible by re-editing the event. Confidence is high because the description clearly indicates data modification without irreversible side effects.
From the tool's definition 'Update an existing event in Google Calendar. Can modify title, time, location, description, and attendees.' This describes reversible modification of calendar data.
Attacks that exploit this kind of access
The rule that runs calendar_update_event safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For calendar_update_event, this is the rule to start with:
calendar_update_event 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 Dialogbrain, apply this rule, and every calendar_update_event call is checked against it from then on.
Questions about calendar_update_event
Update an existing event in Google Calendar. Can modify title, time, location, description, and attendees. Only specified fields will be updated. It is categorised as a Write tool in the Dialogbrain MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
calendar_update_event accepts 8 parameters: end, start, summary, event_id, location, attendees, calendar_id, description. Required: event_id. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for calendar_update_event: 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 Dialogbrain. Nothing to install.
calendar_update_event 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 calendar_update_event 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 calendar_update_event. 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.
calendar_update_event is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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