AI agents use update_demand_endpoint 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 | Demand endpoint ID |
name | string | — | Demand endpoint name |
status | string | — | Whether to send bid requests |
priority | string | — | Serving priority |
bid_floor | number | — | Default CPM bid floor |
geo_target | number | — | Geo target ID |
filter_type | string | — | Zone filtering type |
allowed_sizes | array | — | Allowed zone sizes |
demand_source | number | — | Demand Source ID |
revenue_share | number | — | Revenue share percentage |
filtered_zones | array | — | Zone IDs for filter list |
markup_percent | number | — | Markup percent |
Parameters from the server's own tool schema.
This tool modifies ad campaign infrastructure by updating demand endpoint settings. While reversible (Write rather than Destructive), misuse could redirect ad traffic, modify integrations, or disrupt campaign delivery. Severity is medium because the blast radius is limited to endpoint configuration rather than financial transactions or irreversible data loss, though it could impact ad delivery operations.
From the tool's definition Tool name 'update_demand_endpoint' and description 'Update an existing demand endpoint' indicate modification of existing configuration data.
Risk signalsHigh parameter count (16 properties)
Attacks that exploit this kind of access
Update an existing demand endpoint. 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_demand_endpoint accepts 12 parameters: id, name, status, priority, bid_floor, geo_target, filter_type, allowed_sizes, demand_source, revenue_share, filtered_zones, markup_percent. 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_demand_endpoint: 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_demand_endpoint 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_demand_endpoint 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_demand_endpoint. 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_demand_endpoint 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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