update_campaign_assignment
Update an existing campaign assignment
This record as markdown: /tools/adbutler/update-campaign-assignment.md
What update_campaign_assignment does on AdButler
AI agents use 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 | Campaign assignment ID |
active | boolean | — | Whether assignment is active |
weight | number | — | Relative delivery weight |
keywords | string | — | Comma-separated keywords |
schedule | number | — | Schedule ID |
geo_target | number | — | Geo Target ID |
list_target | number | — | List Target ID |
data_key_target | number | — | Data Key Target ID |
platform_target | number | — | Platform Target ID |
keywords_match_method | string | — | Keyword matching method |
Parameters from the server's own tool schema.
Why update_campaign_assignment is rated Medium
This tool modifies existing campaign assignment data, which is a Write operation. It is reversible (can be updated again), so it does not qualify as Destructive. The severity is medium because incorrect campaign assignment updates could impact ad delivery, revenue tracking, or publisher relationships, but the effect is limited to campaign configuration rather than permanent deletion or financial transactions.
From the tool's definition Tool name 'update_campaign_assignment' combined with description 'Update an existing campaign assignment' indicates modification of campaign configuration data.
Risk signalsHigh parameter count (10 properties)
Attacks that exploit this kind of access
The rule that runs update_campaign_assignment safely
PolicyLayer is an MCP gateway: it sits between your AI agents and AdButler, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_campaign_assignment, this is the rule to start with:
update_campaign_assignment 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 AdButler, apply this rule, and every update_campaign_assignment call is checked against it from then on.
Questions about update_campaign_assignment
Update an existing 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.
update_campaign_assignment accepts 10 parameters: id, active, weight, keywords, schedule, geo_target, list_target, data_key_target, platform_target, keywords_match_method. 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_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.
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 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 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.
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.
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