AI agents use update_day_parting to create or update resources in AdButler — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AdButler environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
id | number | Yes | Day parting ID |
name | string | — | Day parting name |
ranges | object | — | Object mapping day names (monday-sunday) to arrays of time ranges |
is_template | boolean | — | If true, shown in UI when creating/editing schedules |
use_member_timezone | boolean | — | If true, use account timezone; if false, use viewer timezone |
Parameters from the server's own tool schema.
This tool modifies advertising campaign settings (day parting rules) reversibly. Updates are not destructive—the previous rule can be replaced or reverted. It does not delete data, execute code, or involve financial transactions.
From the tool's definition Tool name is 'update_day_parting' and description states 'Update an existing day parting rule'. Day parting rules control when ads are displayed (by time/day). The 'update' verb indicates modification of existing configuration data.
Attacks that exploit this kind of access
Update an existing day parting rule. It is categorised as a Write tool in the AdButler MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_day_parting accepts 5 parameters: id, name, ranges, is_template, use_member_timezone. Required: id. The full parameter table on this page comes from the server's own tool schema.
Register the AdButler MCP server in PolicyLayer and add a rule for update_day_parting: 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 AdButler. Nothing to install.
update_day_parting 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 update_day_parting 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 update_day_parting. 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.
update_day_parting is provided by the AdButler MCP server (adbutler/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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