Mcp Company Headcount Estimator

com.mambabuiltPublished by mambabuilt.comv1.0.1Updated Nov 7, 2026

Employee count band for a company domain, with source and confidence. No LinkedIn login.

VerifiedSTDIODesktop onlyWeb Search & ScrapingBusiness & Commerce

Overview

AI-generated overview

Estimates a company's employee count band from its website domain, returning the source, confidence and supporting context via an Apify actor.

What you can do
  • Estimate employee headcount bands for one domain or up to 500 domains in a batch
  • Return band ranges, an exact count when a source gives one, the estimate source, a confidence score and whether sources agree
  • Report rows with no size as no_data at no charge
  • Include GitHub public member counts and open jobs as context
  • Limit which sources are consulted (LinkedIn search snippets, Wikidata, homepage, GitHub, jobs) and optionally cap run cost
When to use it
Useful when you need quick company size estimates for lead qualification, market research or filtering a list of domains by headcount band, without logging into LinkedIn.
Requirements
Runs locally as an npm package via npx, so Node.js 18 or newer is needed. Requires an Apify account and an Apify API token in the APIFY_TOKEN environment variable; the tool is listed without a token but calls need one. An optional GITHUB_TOKEN raises GitHub member-count limits on large batches. Network access to Apify is required.
Before you install
Calls are billed per event to your Apify account: a charge per row that returns an employee band and a small per-run start fee, with cached, no-data and error rows free. The APIFY_TOKEN is a paid-account credential and should be kept private. Results are estimates with a confidence score, not verified figures, and the server sends domains to Apify for processing.

Installation

In SourceWeft

  1. Open Mcp Company Headcount Estimator in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Company Headcount Estimator MCP Server

[Glama score] [MCP Registry] [npm version] [npm downloads] [license] [mcpservers.org]

[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

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:

json
{  "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:

json
{  "domains": ["Linear | linear.app", "posthog.com", "clay.com"]}

Inputs

Every buyer facing input of the actor. Omitted inputs take the actor's own defaults.

InputTypeDescription
domainstringOne company domain
company_namestringThe name for that one domain; empty reads it from the homepage
domainsarrayUp to 500 domains; Name | domain.com passes the name
sourcesarrayAny of linkedin, wikidata, homepage, github, jobs; empty means all
skip_cachestringtrue or false. Default false; a row from the last 7 days comes back free
max_charge_usdstringOptional 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.

EventFree planBronzeSilverGold
company-estimated, per row with an employee band$0.036$0.0342$0.0324$0.0306
apify-actor-start, per run start (one per GB of run memory)$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.

Source: README.md at commit f0230fc

Tools

1

estimate_company_headcount

Estimate company headcount

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.

Parametersdomaindomainssourcesskip_cachecompany_namemax_charge_usd

Version history

2
  1. v1.0.1LatestNov 5, 2026
  2. v1.0.0Oct 22, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts
  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts