AI agents use draft_update_campaign_assignment 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 | Draft campaign assignment ID |
draft | object | — | Object containing campaign assignment fields to update |
Parameters from the server's own tool schema.
This tool modifies campaign assignment data. Since it operates on a draft (pre-publication state), the change is reversible and can be undone, placing it in Write rather than Destructive. The blast radius is medium because a misconfigured campaign assignment could affect ad delivery and monetization, but the change is not irreversible and not financial in nature (no payments or funds movement).
From the tool's definition Tool name explicitly states 'update' and description says 'Update an existing draft campaign assignment'—direct modification of data. The 'draft' qualifier suggests the change is reversible until publication.
Attacks that exploit this kind of access
Update an existing draft campaign assignment. 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.
draft_update_campaign_assignment accepts 2 parameters: id, draft. 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 draft_update_campaign_assignment: 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.
draft_update_campaign_assignment 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 draft_update_campaign_assignment 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 draft_update_campaign_assignment. 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.
draft_update_campaign_assignment 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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