LinkedIn Ads MCP Server

get_campaign_analytics

Retrieve performance metrics for LinkedIn ad campaigns over a specified date range, including impressions, clicks, cost, and conversions.

Instructions

Pull performance metrics for one or more campaigns over a date range.

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": {
      "campaignIds": "<campaignIds>",
      "dateRange": "<dateRange>"
    },
    "name": "get_campaign_analytics"
  }
}

Input Schema

Name	Required	Description	Default
`campaignIds`	Yes	Campaign URNs
`dateRange`	Yes
`granularity`	No		DAILY
`fields`	No	Metric fields to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 3, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description carries full burden for behavioral transparency, but it only states the function. It does not disclose whether the operation is read-only (though implied), any permissions required, rate limits, or how results are aggregated.

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?

A single sentence conveys the core function without extraneous words, making it concise and front-loaded.

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

Completeness2/5

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

The description lacks details about the return format, pagination, or how to interpret the metrics. Given no output schema, this information would be valuable for an agent to correctly use the tool.

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

Parameters3/5

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

The input schema has 4 parameters with partial descriptions (50% coverage). The description adds general context (performance metrics over date range) but does not elaborate on each parameter beyond what the schema provides. The baseline of 3 is appropriate given the coverage.

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 it pulls performance metrics for one or more campaigns over a date range, effectively distinguishing it from sibling tools like get_campaign (single campaign) and list_campaigns (list without metrics).

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or suggest other tools like get_campaign for detailed campaign data.

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