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Search LinkedIn ads

search_linkedin_ads

Search LinkedIn's Ad Library by company, keyword, or company ID to pull targeted B2B ads and real impression counts. Returns compact JSON with creative, CTA, media, and dates.

Instructions

Structured LinkedIn Ad Library search by company name, keyword, or companyId — use for a targeted B2B pull; use research_ads for open-ended research. Returns compact JSON {advertiser, headline, description, cta, link, media, dates, impressions} per ad — LinkedIn is the one library exposing real impression counts. Spends about a credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNomax ads returned (1–25, default 8)
companyNoadvertiser company name
keywordNokeyword across all advertisers
companyIdNoLinkedIn company id (numeric) when the name is ambiguous
countriesNoCSV of 2-letter codes like 'US,CA'; omit or 'ALL' = worldwide

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.161
    • changedOutput schema / (root)
      Previous value: -{
-  "$schema": "http://json-schema.org/draft-07/schema#",
-  "additionalProperties": false,
-  "properties": {
-    "ads": {
-      "description": "the compact ad objects ({advertiser, headline, description, cta, link, media, dates, impressions})",
-      "items": {},
-      "type": "array"
-    },
-    "found": {
-      "description": "total ads found upstream",
-      "type": "number"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. Addedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Goes beyond the annotations by disclosing a cost ('Spends about a credit') and a notable capability (real impression counts, unique to LinkedIn). It does not explain why readOnlyHint=false / idempotentHint=false for what looks like a search (presumably the credit spend), but there is no contradiction and the credit disclosure is genuinely useful.

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?

Three tight sentences, front-loaded with the purpose and routing before the return shape and cost. Dense but every clause carries information; minor cost is that the return-field list is a long inline enumeration.

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?

With no output schema, the description supplies the return shape ({advertiser, headline, description, cta, link, media, dates, impressions}), the cost, and the routing alternative — everything needed to call and interpret the tool correctly.

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?

Schema description coverage is 100%, so all five parameters are already documented (including the countries CSV and companyId ambiguity hint). The description only restates the targeting options at a high level, adding no syntax or format detail beyond the schema. Baseline 3.

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?

States a specific verb and resource ('Structured LinkedIn Ad Library search') plus the three targeting axes (company name, keyword, companyId), which lets an agent distinguish it from the ad-search siblings at a glance.

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

Usage Guidelines5/5

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

Explicitly names the alternative ('use research_ads for open-ended research') and the condition that selects this tool ('a targeted B2B pull'). This is exactly the when/when-not routing an agent 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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