linkedin_get_company
Fetch one company's LinkedIn page: name, description, industry, employee count, headquarters, website, founding year, specialities, and the URN/numeric id you need for linkedin_search_people company filters. identifier accepts a company URL, the slug after /company/ (e.g. 'microsoft'), or a website domain like 'microsoft.com'; numeric ids and URNs are search-filter inputs, not fetch identifiers. Domains are resolved to a company and verified against that company's website: a domain identifier always QUOTES base+4 credits (set max_credits accordingly), and the 4-credit resolution surcharge is refunded at settlement when the domain was resolved before, so known domains settle at the base price. A domain that cannot be verified to a company returns INVALID_INPUT with the closest matches instead of a guessed company. Costs 4 credits base. Do not guess a slug from a brand name: slugs are vanity strings and a famous name can belong to an unrelated company's page (linkedin.com/company/anthropic is a small investment fund, not the AI lab). When you only know the company's name, pass its website domain instead -- the verified form -- and sanity-check the returned industry and description against what you expected. This tool does not search by name: if you only have an approximate company name, use linkedin_search_people's current_company filter with keywords (the filter resolves names) or give the exact slug. For the company's posts, use linkedin_get_posts with the same identifier (URL, slug, or website domain all work there too).
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Input Schema
{
"type": "object",
"properties": {
"freshness": {
"type": "string"
},
"identifier": {
"type": "string",
"description": "Company URL, slug (after /company/), or website domain (e.g. 'microsoft.com'). Numeric ids/URNs are not fetchable; use them only in linkedin_search_people company filters."
},
"max_credits": {
"type": "number"
}
}
}