Google Ads MCP Server

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create_campaign

Create a new Google Ads campaign with specified settings, saved in paused status for safety. Set name, budget, channel type, or validate with dry run.

Instructions

Create a new Google Ads campaign.

Creates a new campaign with the specified settings. For safety, campaigns are created in PAUSED status by default - use enable_campaign to start them.

Args: name: Campaign name customer_id: Target customer ID (optional if set in config) budget_amount_micros: Daily budget in micros (1,000,000 = $1.00). Default is $10/day. advertising_channel_type: Channel type - SEARCH, DISPLAY, SHOPPING, etc. dry_run: If True, validate but don't execute the operation

Returns: Result with success status, resource_name, and campaign_id

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "create_campaign"
  }
}

Input Schema

Name	Required	Default
`name`	Yes
`customer_id`	No
`budget_amount_micros`	No
`advertising_channel_type`	No	SEARCH
`dry_run`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 28, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description fully discloses default paused status, dry_run behavior, default budget, and return structure. No contradictory or hidden destructive traits are mentioned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-organized with a succinct intro, bulleted args, and return section. Efficient but could be slightly more compact without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Fully covers 5 parameters, safety behavior, dry_run, and return values given no annotations and no enum constraints. Output schema handles return details, but description adds sufficient context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, description compensates by explaining each parameter in detail, including examples for budget_amount_micros and advertising_channel_type, and defaults beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Create a new Google Ads campaign' and elaborates on creating campaigns with specific settings. It distinguishes from sibling tools like enable_campaign by noting campaigns start in PAUSED status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises using enable_campaign after creation, providing a clear workflow. Mentions dry_run for validation but lacks explicit when-not-to-use guidance for other scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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