paid_ads_optimizer

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io

Medium RISK CLASS

Category Write

Parameters 65 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/paid-ads-optimizer.md

WHAT IT DOES

What paid_ads_optimizer does on Mcp Knowledge

AI agents use paid_ads_optimizer to create or update resources in Mcp Knowledge, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Knowledge environment.

Parameter	Type	Required	Description
`async`	boolean	—	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti
`company`	object	Yes
`campaigns`	array	Yes
`targetMetric`	string	Yes
`audienceDescription`	string	Yes
`totalMonthlyBudgetEur`	number	Yes

Parameters from the server's own tool schema.

RISK

Why paid_ads_optimizer is rated Medium

This tool writes or updates ad campaign configurations and spending strategies based on optimization logic. Although it influences financial outcomes (ad spend), it does not directly move money or commit financial obligations—it recommends or implements changes to existing ad campaigns. The primary action is modification of ad settings/strategy (Write), not financial transaction execution.

From the tool's definition Tool describes itself as an 'optimizer' that returns 'structured, audited deliverable' and references a case with '€9k/mo gaspillés identifiés' (identified wasted spend).

Risk signalsHigh parameter count (13 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs paid_ads_optimizer safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For paid_ads_optimizer, this is the rule to start with:

paid_ads_optimizer Rate-limited

paid_ads_optimizer 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "paid_ads_optimizer": {
      "limits": [
        {
          "counter": "paid_ads_optimizer_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every paid_ads_optimizer call is checked against it from then on.

FAQ

Questions about paid_ads_optimizer

What does the paid_ads_optimizer tool do? +

Optimiseur de publicités payantes — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Spendesk (Google + LinkedIn · €45k/mo) — €9k/mo gaspillés identifiés · ROAS LinkedIn ×2.4. Inputs are validated server-side — send the documented case fields. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does paid_ads_optimizer accept? +

paid_ads_optimizer accepts 6 parameters: async, company, campaigns, targetMetric, audienceDescription, totalMonthlyBudgetEur. Required: company, campaigns, targetMetric, audienceDescription, totalMonthlyBudgetEur. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on paid_ads_optimizer? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for paid_ads_optimizer: 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 Mcp Knowledge. Nothing to install.

What risk level is paid_ads_optimizer? +

paid_ads_optimizer is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit paid_ads_optimizer? +

Yes. Add a rate_limit block to the paid_ads_optimizer 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.

How do I block paid_ads_optimizer completely? +

Set action: deny in the PolicyLayer policy for paid_ads_optimizer. 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.

What MCP server provides paid_ads_optimizer? +

paid_ads_optimizer is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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