{
"name": "searchapi_linkedin_ad_library",
"description": "LinkedIn Ad Library results from SearchApi, as structured JSON.",
"input_schema": {
"type": "object",
"properties": {
"q": {
"type": "string",
"description": "Search query; most engines accept native operators and advanced filters."
},
"company": {
"type": "string",
"description": "Advertiser/company name filter."
},
"country": {
"type": "string",
"description": "Country the ads were shown in."
},
"next_page_token": {
"type": "string",
"description": "Opaque token from the previous response that fetches the next page."
}
},
"required": []
}
}Paste the definition into your own agent's tools array. The schema is generated from this engine's catalog entry, and the reader's configured values ride in the schema's examples. The name is ours rather than the MCP server's — it is what your agent will call — and every engine's is prefixed searchapi_.