# Company Email Finder (`spookyweb/company-email-finder`) Actor

Find the contact addresses a company publishes, work out its email naming convention, verify the domain can receive mail, and generate addresses for named people. One charge per domain, whatever the site size.

- **URL**: https://apify.com/spookyweb/company-email-finder.md
- **Developed by:** [丂卩ㄖㄖҜㄚ](https://apify.com/spookyweb) (community)
- **Categories:** Lead generation, Integrations, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $21.00 / 1,000 domain analyseds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Company Email Finder

Give it a company domain and it returns the contact addresses that company publishes, the email naming convention behind them, an MX check on the domain, and generated addresses for people you name.

### 🔍 What does Company Email Finder do?

It crawls a company's own website, collects the email addresses published on it, classifies each one, works out the naming pattern the company uses, and checks the domain can actually receive mail. Supply a list of names and it generates the likely address for each from that pattern.

Contact, about and team pages are tried first, so a low page budget still lands on the pages that carry addresses. One charge per domain, whatever the size of the site.

### 📊 What data can I extract?

One record per domain, in this shape:

```json
{
  "domain": "example.com",
  "emailsFound": 6,
  "personalEmails": 2,
  "roleEmails": 3,
  "unclassifiedEmails": 1,
  "emails": [
    { "email": "jane.smith@example.com", "type": "personal", "isFreeProvider": false },
    { "email": "info@example.com", "type": "role", "isFreeProvider": false }
  ],
  "pattern": "first.last",
  "patternConfidence": 1,
  "patternBasedOn": 2,
  "mxValid": true,
  "mxRecords": ["aspmx.l.google.com"],
  "generatedEmails": [
    { "firstName": "Bob", "lastName": "Jones", "email": "bob.jones@example.com", "pattern": "first.last" }
  ],
  "pagesCrawled": 8
}
```

### 💡 Why find company emails?

**B2B outreach.** Build a contact list from what companies publish themselves, with role and personal addresses kept apart so your first line lands right.

**Sales research.** Work out the naming convention at an account, then generate the address for the person you already know you need.

**List hygiene.** Use the MX check to drop dead domains before they burn your sender reputation.

**Recruitment.** Reach hiring contacts at companies that publish a careers or team page.

### 🚀 How do I use Company Email Finder?

1. Click **Try for free**.
2. Put a company domain into `domain`, or a list into `domains`.
3. Add `people` with first and last names if you want addresses generated.
4. Set `maxPagesPerDomain` and leave `verifyMx` on, then click **Start**.
5. Download the results as JSON, CSV or Excel, or pull them from the API.

### ⬇️ Input

```json
{
  "domain": "monzo.com",
  "maxPagesPerDomain": 8,
  "verifyMx": true
}
```

| Field | Type | Default | What it does |
|---|---|---|---|
| `domain` | string | `apify.com` | One company domain, protocol and www optional |
| `domains` | array | | A list of domains, each charged separately |
| `people` | array | | Names to generate addresses for, first and last name, for example `[{ "firstName": "Jane", "lastName": "Smith" }]` |
| `maxPagesPerDomain` | integer | `8` | Pages to crawl per domain, maximum 15 |
| `verifyMx` | boolean | `true` | Run a DNS MX check on the domain |

### ⬆️ Output

#### Table view

Results arrive as a Domains table you can sort and filter in the Console, with the domain, how many addresses were found, the addresses themselves, the inferred pattern, its confidence, the MX result and the page count lined up per domain.

#### JSON

A typical row:

```json
{
  "domain": "monzo.com",
  "emailsFound": 1,
  "emails": [
    { "email": "help@monzo.com", "local": "help", "domain": "monzo.com", "type": "role" }
  ],
  "pattern": "first.last",
  "mxValid": true,
  "pagesCrawled": 2,
  "personalEmails": 0,
  "roleEmails": 1
}
```

Download it from the run as JSON, CSV or Excel, or read it straight from the API.

### Three types, not two

Most tools split addresses into "personal" and "role". That is not enough, and
getting it wrong is expensive: it tells you a department mailbox is a named
human, and your first line lands wrong.

| Type | Meaning |
|---|---|
| `role` | A known department word: info, sales, support, careers |
| `personal` | Name shaped, two parts around a separator: `jane.smith`, `j.smith` |
| `unclassified` | Genuinely ambiguous, a single word that could be either |

`solar@`, `heat@` and `greg@` are all single words. Two are departments, one is
a person, and nothing in the address tells you which. So they come back
`unclassified` rather than guessed at.

### Pattern inference

Supply `people` with first and last names. Where one of them already has a
published address, the convention is inferred from it and used to generate the
rest.

`patternConfidence` is the share of known people the winning convention
explains. Below 0.5, no single address is returned. Instead you get every
candidate, because a confident wrong address is worse than a list.

Conventions covered: `first.last`, `firstlast`, `flast`, `first_last`,
`first-last`, `firstl`, `lastf`, `last.first`, `first`.

### MX verification

A DNS MX lookup, free and fast, tells you whether the domain can receive mail
at all. `mxValid` is `true`, `false`, or `null` when the check was not run or
the lookup itself failed. Null is not the same as false and the two are never
merged.

This is not per-address SMTP verification. It rules out dead domains, not
individual mailboxes.

### Limits

It reads publicly published pages. It does not use a paid enrichment database,
so it finds what a company chose to put on its own website, and nothing more. A
domain with no published addresses returns none, which is a real finding rather
than a failure.

No API keys, no accounts, no proxies.

### 💰 How much does it cost?

| Event | Price |
|---|---|
| Domain analysed | $0.035 |

Charged once per domain. One charge covers all of it: the crawl, the
classification, the pattern inference, the MX check and any generated addresses.

The price does not move with how many addresses a site publishes, how many pages
were read, or how many addresses were generated, so a company with a large team
page costs the same as one with a single contact form.

### 🔌 Integrations

Send results straight to Google Sheets, Slack, Airtable, Zapier, Make or your own webhook using [Apify integrations](https://docs.apify.com/platform/integrations). You can also trigger a run whenever something happens in another tool.

### 🔗 Using Company Email Finder with the Apify API

```bash
curl -X POST "https://api.apify.com/v2/acts/spookyweb~company-email-finder/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"domain": "monzo.com", "maxPagesPerDomain": 8, "verifyMx": true}'
```

Or with the Apify client:

```js
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('spookyweb/company-email-finder').call({
  domain: 'monzo.com',
  maxPagesPerDomain: 8,
  verifyMx: true,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
```

Full detail is in the [Apify API reference](https://docs.apify.com/api/v2), and every run is also callable from the [Python](https://docs.apify.com/api/client/python) and [JavaScript](https://docs.apify.com/api/client/js) clients.

### ❓ FAQ

#### How is the address pattern worked out?

From the addresses the company already publishes. Where a published address matches a person you supplied in `people`, the convention behind it is inferred and applied to the others. `patternConfidence` is the share of known people the winning convention explains, and `patternBasedOn` says how many addresses it was inferred from.

#### What does MX validation check?

Whether the domain has mail exchanger records in DNS, which tells you it can receive mail at all. It is free and fast. `mxValid` is `true`, `false`, or `null` when the check was not run or the lookup itself failed, and null is never merged into false. It is not per-address SMTP verification, so it rules out dead domains rather than individual mailboxes.

#### What is the difference between a personal and a role address?

A role address is a known department word such as info, sales, support or careers. A personal address is name shaped, two parts around a separator, such as `jane.smith` or `j.smith`. Anything that is a single word could be either, so it comes back `unclassified` rather than guessed at. Calling a department mailbox a named human is the expensive direction of that mistake.

#### Can I predict an address for a named person?

Yes, put them into `people` with a first and last name. If the pattern is confident, you get one generated address each. Below a confidence of 0.5 you get every candidate instead of a single answer, because a confident wrong address is worse than a list.

#### How many pages does it read per domain?

`maxPagesPerDomain` decides, default 8 and maximum 15. Contact, about and team pages are tried first, so even a low budget lands on the pages that actually carry addresses. The page count that was used comes back in `pagesCrawled`.

#### What if a domain publishes no addresses?

You get a record with none found. That is a real finding rather than a failure: it tells you the company publishes no contact addresses on its own website. This does not fall back to a paid enrichment database, so it never invents what the site does not show.

### ⚖️ Is it legal to use Company Email Finder?

This reads addresses a company has chosen to publish on its own website, which is business contact information rather than personal data in most cases. It does not guess at private mailboxes and it does not use breach data.

Where an address identifies a named person, UK GDPR applies and you are the data controller for what you do next. You need a lawful basis, typically legitimate interest for B2B contact, and you must honour opt outs. Apify's [ethical scraping guide](https://blog.apify.com/is-web-scraping-legal/) covers the wider picture.

### 👍 Your feedback

Found a bug, or want a field that is not here yet? Open an issue on the Actor's Issues tab. Requests that make the data more useful get built, and problems get fixed quickly.

### 🔎 You might also like

| Actor | What it does |
|---|---|
| [Website Contact Scraper](https://apify.com/spookyweb/website-contact-scraper) | Emails, phones, socials and addresses from company websites, one record per domain |
| [UK Food Hygiene Ratings](https://apify.com/spookyweb/uk-food-hygiene-ratings) | Food hygiene ratings for every UK food business, straight from the FSA |
| [UK Planning Applications](https://apify.com/spookyweb/uk-planning-applications) | Planning applications from every UK council in one feed, with applicant and agent details |

# Actor input Schema

## `domain` (type: `string`):

The company website, for example example.com. Protocol and www are optional.

## `domains` (type: `array`):

Analyse several companies in one run. Each is charged separately.

## `people` (type: `array`):

Objects with firstName and lastName. Their address is generated from the inferred convention where one is found.

## `maxPagesPerDomain` (type: `integer`):

Contact, about and team pages are tried first, so a low budget still lands on the useful ones.

## `verifyMx` (type: `boolean`):

Looks up MX records. Free and fast, and rules out domains that cannot accept email at all.

## Actor input object example

```json
{
  "domain": "apify.com",
  "people": [
    {
      "firstName": "Jane",
      "lastName": "Smith"
    }
  ],
  "maxPagesPerDomain": 8,
  "verifyMx": true
}
```

# Actor output Schema

## `results` (type: `string`):

One row per item: domains with the emails and pattern found.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "domain": "apify.com",
    "people": [
        {
            "firstName": "Jane",
            "lastName": "Smith"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("spookyweb/company-email-finder").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "domain": "apify.com",
    "people": [{
            "firstName": "Jane",
            "lastName": "Smith",
        }],
}

# Run the Actor and wait for it to finish
run = client.actor("spookyweb/company-email-finder").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "domain": "apify.com",
  "people": [
    {
      "firstName": "Jane",
      "lastName": "Smith"
    }
  ]
}' |
apify call spookyweb/company-email-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,spookyweb/company-email-finder"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/RVntly4HiBAOg2m8y/builds/gUrNzpsGGBYbOIlbU/openapi.json