Company Headcount Estimator MCP Server
Estimate company headcount bands from website domains via an Apify-backed MCP tool.
Estimate one company domain or up to 500 domains in a batch, optionally with company names.
Use sources such as LinkedIn search snippets, Wikidata, homepage structured data, GitHub public members, and open jobs.
Return employee bands, band min/max, exact employee count when available, source, confidence, source agreement, and context columns.
Get no-data rows for free with row_status no_data.
Re-run sources with skip_cache, cap run cost with max_charge_usd, and filter checked sources.
Requires APIFY_TOKEN; optional GITHUB_TOKEN improves GitHub member counts. The tool is read-only and Apify bills per estimated company.
Retrieves GitHub public member counts and open jobs as context for company headcount estimation, using an optional GitHub token to raise rate limits on large batches.
Reads LinkedIn company size as printed in Google search results to estimate employee headcount bands for a domain, without directly requesting linkedin.com.
Queries Wikidata for employee counts on items whose official website matches the company domain, contributing to headcount estimates.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Company Headcount Estimator MCP Server How many employees does linear.app have?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Company Headcount Estimator MCP Server
An MCP server for the Mamba Labs Company Headcount Estimator actor on Apify. Give it a company domain or a list. Each domain returns an employee count band with the source it came from and a confidence score.
What's Inside
Related MCP server: Company Firmographic Enricher MCP Server
What it does
For each domain the actor reads, in order: the LinkedIn company size as Google prints it in its search results (a result counts only when it shows the domain as the company website; no request goes to linkedin.com), the employee count on Wikidata for the item whose official website is the domain, and the numberOfEmployees the homepage declares. It returns employee_band, employee_band_min, employee_band_max, an exact employee_count when a source gives one, estimate_source, confidence (0 to 1), and sources_agree, plus GitHub public members and open jobs as context. Rows with no size come back free with row_status no_data.
All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.
Quick start
You need Node.js 18 or newer and an Apify account with an API token.
Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:
{
"mcpServers": {
"mamba-company-headcount-estimator": {
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-company-headcount-estimator"
],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Restart the client. The estimate_company_headcount tool appears.
Prerequisites
Node.js 18 or newer.
An Apify API token from console.apify.com/account/integrations, set as
APIFY_TOKEN. The server lists its tool without a token; a call needs one.Optional:
GITHUB_TOKEN, your own free GitHub token, for GitHub member counts on large batches.
Example prompts
"How many employees does linear.app have?"
"Estimate the headcount band for these 20 domains and keep only the ones with 51 to 500 staff."
"Which of these companies have more than 1,000 employees, and how sure is each answer?"
Tool
estimate_company_headcount. One tool. Example arguments:
{
"domains": ["Linear | linear.app", "posthog.com", "clay.com"]
}Inputs
Every buyer facing input of the actor. Omitted inputs take the actor's own defaults.
Input | Type | Description |
| string | One company domain |
| string | The name for that one domain; empty reads it from the homepage |
| array | Up to 500 domains; |
| array | Any of |
| string | true or false. Default false; a row from the last 7 days comes back free |
| string | Optional cost cap for the run |
The actor's github_token input is filled from this server's GITHUB_TOKEN environment variable when it is set.
Pricing
Pay per event on Apify, billed to your Apify account. Prices in USD.
Event | Free plan | Bronze | Silver | Gold |
| $0.036 | $0.0342 | $0.0324 | $0.0306 |
| $0.0015 | $0.0015 | $0.0015 | $0.0015 |
No data, invalid input, error, and cached rows are free.
Your keys
The actor needs no key. A GitHub token is optional and only raises the GitHub limit for member counts. Proxy traffic and Google result pages add nothing to your price: Mamba Labs pays the platform costs of the run.
Full actor documentation
apify.com/mambalabs/company-headcount-estimator
License
MIT. See LICENSE.
Available Tools
1 toolestimate_company_headcountEstimate company headcountARead-onlyIdempotent
Estimate the employee count band of a company from its website domain. Give domain (for example linear.app) or domains (up to 500, one per item, Name | domain.com to pass a name). Each domain returns one row: employee_band (1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, or 10001+), employee_band_min and employee_band_max, an exact employee_count when Wikidata or the homepage gives one, estimate_source (linkedin_search_snippet: the LinkedIn company size as Google prints it in its results, matched by the website the result shows; wikidata; or homepage_structured_data), a 0 to 1 confidence, sources_agree, and context columns (GitHub public members, open jobs). No request goes to linkedin.com. Rows with no size come back free with row_status no_data. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN; Apify charges per estimated company.
Inputs: domain, domains, sources, skip_cache, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
The server exposes only one tool, so there is no risk of selecting the wrong operation. Its purpose—estimating company headcount from domains—is clear and unambiguous.
The single tool name, estimate_company_headcount, follows a clear verb_noun convention. There are no competing names or mixed styles to create inconsistency.
The server is a focused, single-purpose headcount estimator, and one tool is sufficient for that scope. Batch input support means the single tool can handle both individual and bulk requests without needing extra tools.
For its stated purpose, the tool covers the core operation thoroughly: batch domains, band output, exact counts when available, confidence, sources, and error reporting. Minor gaps could exist around richer validation or follow-up operations, but the core estimator surface is complete.
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