LinkedIn Company Employee API and MCP — Search People at a Company
Give it one or more company pages and it searches the people associated with them, with the same filters you would use on a general people search: job title, seniority, function, location, years of experience and headcount band.
- You send
- One or more company pages, with optional people filters
- You get back
- People at those companies with titles, profiles and locations
- Coverage
- People associated with companies that have a public profile.
- Price
- 30 points per run, plus 10 per profile — $0.03 per run plus $0.01 per profile
- A per-run charge plus a per-profile charge. A run that returns nobody is charged only the run.
Ways to get this data
Three approaches teams use today, and where each one runs into trouble.
| Approach | What it takes | Cost | Trade-off |
|---|---|---|---|
| Browsing the company's people tab | Scroll and copy, account by account | Free, and slow | Falls apart past a handful of accounts |
| An org-chart product | Another subscription with its own coverage gaps | Per seat | Inferred hierarchies look authoritative and are frequently wrong |
| NeuralVerge | One request per set of companies | 30 points per run plus 10 per profile | A filtered sample of an organisation, not a guaranteed complete roster |
What you get back
Every field in the example response below.
| Field | Type | Description |
|---|---|---|
total_items | number | How many people came back. |
first_item | object | The first matched person. |
first_item.firstName | string | First name. |
first_item.lastName | string | Last name. |
first_item.profileUrl | string | Profile URL. |
first_item.title | string | Job title. |
first_item.company | string | The company they were matched at. |
first_item.location | string | Where they are based. |
items | array | The matched people in result order. Entries carry firstName, lastName and profileUrl in the example. |
Example response
A real response, as returned.
{
"session_id": "11111111-1111-1111-1111-111111111111",
"verification_type": "data_source",
"kind": "linkedin_company_employee",
"companies": [
"https://www.linkedin.com/company/openai/"
],
"searchQuery": "Recruiter",
"maxResults": 3,
"startPage": 2,
"scraperMode": "full",
"locations": [
"Amsterdam"
],
"currentJobTitleFilter": [
"Recruiter"
],
"pastJobTitle": [],
"yearsOfExperienceFilter": [],
"yearsAtCurrentCompanyFilter": [],
"seniorityLevelFilter": [],
"functionFilter": [],
"industryIds": [],
"companyHeadcountFilter": [],
"human": "# LinkedIn company employees\n\n**Companies:** https://www.linkedin.com/company/openai/\n- **Results returned:** 3\n\n### Jane Doe\n\n- **Profile URL:** https://www.linkedin.com/in/jane-doe/\n- **First name:** Jane\n- **Last name:** Doe\n- **Title:** Recruiter\n- **Company:** OpenAI\n- **Location:** Amsterdam\n- **Summary:** Technical recruiting across research and engineering roles.",
"machine": {
"total_items": 3,
"first_item": {
"firstName": "Jane",
"lastName": "Doe",
"profileUrl": "https://www.linkedin.com/in/jane-doe/",
"title": "Recruiter",
"company": "OpenAI",
"location": "Amsterdam"
},
"items": [
{
"firstName": "Jane",
"lastName": "Doe",
"profileUrl": "https://www.linkedin.com/in/jane-doe/"
}
]
},
"points_per_run": 30,
"points_per_profile": 10,
"total_points": 60
}How to run it
The same lookup works from the app, the API, or as a tool an agent can call mid-task.
Only `companies` is required, and it takes an array — you can map several accounts in one run and pay the run charge once.
curl -X POST https://api.neuralverge.ai/functions/v1/run-linkedin-company-employee \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"companies": ["https://www.linkedin.com/company/example-company"],
"currentJobTitleFilter": ["Revenue Operations"],
"seniorityLevelFilter": ["Director"],
"maxResults": 25
}'What teams use it for
Where this field shows up in an actual workflow.
Find every relevant role at a target account before the first call.
Identify the other stakeholders when your champion goes quiet.
See how a competitor staffs a function you are also building.
Search candidates across a named set of companies rather than the whole market.
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
People associated with companies that have a public profile.
Searched at request time.
This source returns personal data. Use it for legitimate business purposes under your own lawful basis, honour deletion and opt-out requests, and check the acceptable use policy for what is out of bounds.
- —This is a filtered sample, not a complete or verified staff list.
- —Association is what people publish about themselves, so leavers can linger and joiners can be missing.
- —It does not return a reporting hierarchy — titles are what you get.
Questions, answered
No, and no source honestly claims that. It returns the people who match your filters and publish an association with the company. Read it as a map of the relevant part of an organisation.
Related sources
Try linkedin company employee on your own data
One request format across every source in the catalog.