LinkedIn Ads MCP Server

bulk_create_campaigns

Queue and execute bulk creation of up to 100 LinkedIn ad campaigns, with support for referencing campaign groups created in the same session and enforcement of best practices.

Instructions

Queue and execute bulk creation of campaigns (up to 100). Supports $ref:group_N references to link to groups created in the same session. Best practices are enforced on every campaign.

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": {
      "campaigns": "<campaigns>"
    },
    "name": "bulk_create_campaigns"
  }
}

Input Schema

Name	Required	Description	Default
`campaigns`	Yes
`dryRun`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 3, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the burden. It mentions queuing and execution but lacks details on async behavior, rate limits, failure handling, and what 'best practices enforced' means. Significant gaps remain.

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

Conciseness5/5

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

Two sentences with no redundancy. Key information (limit, ref feature, best practices) is front-loaded and concise.

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

Completeness3/5

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

The tool is complex with many nested fields, yet no output schema is provided. The description does not clarify return values, queuing behavior, or how to check execution status. Sibling tool get_queue_status suggests async processing, but this is not referenced. Completeness is adequate but not thorough.

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

Parameters2/5

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

Schema description coverage is 0% per context signals, so the description must compensate. It adds context about max 100 items and $ref references but does not explain other parameters (e.g., dryRun, campaign fields) beyond what the schema already provides. Limited added value.

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 the tool queues and executes bulk creation of campaigns with a limit of 100, and supports $ref references. It distinguishes from siblings like create_campaign and bulk_update_campaigns.

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

Usage Guidelines3/5

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

The description implies usage for bulk creation but does not explicitly state when to use this tool vs alternatives like create_campaign for single campaigns or bulk_update_campaigns. No exclusions or prerequisites are mentioned.

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