ScrapeCreators MCP Server

Ad Details

linkedin_ad_library_ad_details

Fetches LinkedIn ad details by URL: headline, advertiser, targeting, impressions, dates.

Instructions

Retrieves detailed information about a specific LinkedIn ad by URL. Returns id, description, headline, adType, advertiser, and targeting with language, location, and audience criteria. Also includes totalImpressions, impressionsByCountry, adDuration, startDate, and endDate. Date and impression fields are nullable when LinkedIn does not expose them on the public ad page. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

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": {
      "url": "<url>"
    },
    "name": "linkedin_ad_library_ad_details"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	The url of the ad
`account`	No	Named private ScrapeCreators account; selects credentials, not a remote account ID.
`confirm`	No	Must be true for the specific approved credit-consuming research call.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Oct 2, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With readOnlyHint=false present, the description usefully adds that it 'potentially consumes paid API credits,' that confirm=true is required, and that these read-like POST requests do not publish to social platforms -- directly reconciling the apparent write intent with the annotations. It also discloses nullable date/impression fields, which the annotations do not cover.

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?

Purpose is front-loaded in the first sentence, followed by return fields and then behavioral caveats. The enumeration of returned fields is somewhat list-heavy but each clause is informative and there is no filler.

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

Completeness4/5

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

There is no output schema, so enumerating the returned fields (id, description, headline, adType, targeting, impressions, dates) is necessary and done. Combined with the credit/confirm caveats and nullability note, an agent has enough to call it correctly, though the relationship to the search sibling remains unstated.

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 three parameters are already documented in the schema; the description mostly restates the confirm=true requirement rather than adding new syntax or format meaning. Baseline 3 is appropriate when the schema carries the load.

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 and resource (retrieves detailed info about a specific LinkedIn ad) and anchors the retrieval on a URL, which clearly separates it from the same-platform search sibling linkedin_ad_library_search_ads. It does not explicitly name that sibling or state that search must precede detail retrieval, so it stops short of full sibling differentiation.

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 (you must have a specific ad URL, and confirm=true is required) and flags credit consumption, but it never says when to use this versus linkedin_ad_library_search_ads or the Facebook/Google ad-detail siblings. Usage is inferable from the URL requirement rather than stated.

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

Deploy Server