AI agents use create_schedule 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 |
|---|---|---|---|
end_at | string | — | End date/time in ISO-8601 format, null for indefinite |
end_date | string | — | End date (YYYY-MM-DD HH:MM:SS), null for indefinite — deprecated, use end_at |
start_at | string | — | Start date/time in ISO-8601 format |
quota_type | string | — | Quota measurement type |
start_date | string | — | Start date (YYYY-MM-DD HH:MM:SS) — deprecated, use start_at |
day_cap_type | string | — | Daily cap type |
day_cap_limit | number | — | Daily cap limit (number of views or clicks per day) |
day_parting_id | number | — | Day parting ID for time-of-day targeting |
quota_lifetime | number | — | Total quota amount (views or clicks, not per thousand) |
delivery_method | string | — | Delivery pacing: "default" (ASAP) or "smooth" (evenly distributed) |
end_at_timezone | string | — | IANA timezone for end_at |
start_at_timezone | string | — | IANA timezone for start_at (e.g. "America/New_York") |
Parameters from the server's own tool schema.
This tool creates new schedule records in the AdButler system, which is a write operation. While it modifies ad delivery behavior, the action is reversible (schedules can be edited or deleted). It does not delete data (Destructive), execute arbitrary code (Execute), involve financial transactions (Financial), or trigger irreversible side effects.
From the tool's definition Tool name 'create_schedule' and description 'Create a new schedule' indicate creation of new data. The description specifies this creates scheduling rules for ad delivery that are 'automatically linked to ad items via placements', representing a reversible…
Risk signalsHigh parameter count (15 properties)
Attacks that exploit this kind of access
Create a new schedule for time-based ad delivery. Schedules are automatically linked to ad items via placements. 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.
create_schedule accepts 12 parameters: end_at, end_date, start_at, quota_type, start_date, day_cap_type, day_cap_limit, day_parting_id, quota_lifetime, delivery_method, end_at_timezone, start_at_timezone. 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 create_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 AdButler. Nothing to install.
create_schedule 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 create_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.
Set action: deny in the PolicyLayer policy for create_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.
create_schedule 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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