LinkedIn Ads MCP Server

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Get FAQ

get_faq

Read-onlyIdempotent

Answers common questions about the hosted LinkedIn Ads MCP server, including pricing, safety and approvals, API keys, multiple ad accounts and supported AI apps. Returns Markdown with one heading per question.

Instructions

Get the answers to common questions about the hosted LinkedIn Ads MCP server by AdKit: price, safety and approvals, API keys, several ad accounts and supported AI apps. Use this before answering such a question from memory. Returns Markdown, one heading per question.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 13, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered structurally. The description adds the return format ("Markdown, one heading per question"), which is genuine value beyond the annotations; it does not, however, mention size or latency characteristics.

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?

Three short sentences: what it returns, when to call it, and the output format. Front-loaded with the resource, zero filler, and every sentence carries information an agent needs.

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?

For a zero-parameter, read-only lookup with full annotation coverage, the description supplies purpose, trigger, and return format. There is no output schema, but the Markdown/one-heading-per-question note covers what an agent needs to consume the result.

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

Parameters4/5

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

The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies a single static retrieval with no inputs to supply.

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

Purpose4/5

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

States a specific verb (get) and resource (answers to common questions) and enumerates the covered topics: price, safety and approvals, API keys, multiple ad accounts, supported AI apps. That topic list also separates it from get_setup_guide and get_example_prompts, though no sibling is named explicitly.

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?

"Use this before answering such a question from memory" is an explicit and actionable trigger condition, which is stronger than most definitions provide. It stops short of stating when not to use it or naming a concrete alternative tool for adjacent needs.

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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