Email Verifier & List Cleaner

Verify an email list in bulk before you send anything: syntax, whether the domain exists, whether it accepts mail, and whether it is a throwaway or a team inbox.

Built to sit right after a scraper. You pull 5,000 addresses off the web, run them through here, and keep the ones worth sending to.

How to use

1. Sign up for Apify — the free plan's monthly credit is enough to try this Actor.
2. Open Email Verifier, fill in the input (the form is pre-filled with a working example) and click Start.
3. Watch results stream into the dataset table while the run is going.
4. Export as JSON, CSV, Excel, XML, HTML or RSS — or pull the results from your own code with the Apify API.

What data can this email verification tool check?

Check	What it tells you
Syntax	Malformed addresses, stray characters, double @
Domain resolves	The domain exists at all
MX records	The domain actually accepts mail, and which server handles it
Mail provider	Google Workspace, Microsoft 365, Zoho, Naver Works…
Disposable	mailinator.com and ~3,000 other throwaway domains
Role account	info@, sales@, support@ — goes to a team, not a person
Free provider	Gmail, Yahoo, Naver — useful to drop for B2B
Typo suggestion	gmial.com → gmail.com

Each row ends with a status: valid, risky or invalid, plus the reason in plain words.

How to verify emails in bulk

Field	What it does
emails	The addresses to check
datasetId + datasetEmailField	Or read them straight from another Actor's output
onlyValid	Return only clean addresses — you pay only for those
skipRoleAccounts, skipFreeProviders, skipDisposable	Drop what you don't want

Input reference

Every option at a glance. A minimal input that works as-is:

{
  "emails": [
    "john@stripe.com",
    "info@gmail.com",
    "test@mailinator.com",
    "someone@gmial.com"
  ],
  "datasetEmailField": "email",
  "maxResults": 100000
}

All fields:

• emails (Email addresses) — Addresses to check. Paste a list or connect another Actor's output below.
• datasetId (Or a dataset ID) — Take the addresses from an existing dataset — for example the output of the Website Contact & Email Scraper.
• datasetEmailField (Field with the email) — Which field of that dataset holds the address (or a list of addresses). Default "email".
• onlyValid (Only return valid addresses) — Drop everything that is risky or invalid — you pay only for the addresses you keep. Default false.
• skipRoleAccounts (Drop role accounts) — Remove info@, sales@, support@ and similar team inboxes. Default false.
• skipFreeProviders (Drop free providers) — Remove Gmail, Yahoo, Naver and other personal mailboxes — useful for B2B lists. Default false.
• skipDisposable (Drop disposable addresses) — Remove throwaway domains such as mailinator.com. Default false.
• maxResults (Max results) — Total limit. Default 100000.

What the verified email output looks like

{
  "email": "cto@apify.com",
  "status": "valid",
  "reason": "syntax ok and the domain accepts mail",
  "isSyntaxValid": true,
  "domain": "apify.com",
  "domainExists": true,
  "hasMx": true,
  "mxRecords": [
    "aspmx.l.google.com",
    "alt2.aspmx.l.google.com",
    "alt1.aspmx.l.google.com",
    "aspmx2.googlemail.com",
    "aspmx3.googlemail.com"
  ],
  "mxProvider": "Google Workspace",
  "isDisposable": false,
  "isRoleAccount": false,
  "isFreeProvider": false,
  "suggestion": null,
  "checkedAt": "2026-09-20T12:35:48.645Z"
}

How fast is it and what does it cost?

8 addresses took 5 seconds. DNS lookups are cached per domain, so a list of 5,000 addresses across 300 domains only does 300 lookups.

Honest note about SMTP

Paid verifiers open an SMTP conversation with the mail server to ask whether a specific mailbox exists. This Actor does not do that — outbound SMTP is blocked on the platform it runs on.

What that means in practice: it reliably removes malformed addresses, dead domains, domains that accept no mail, throwaway domains and team inboxes — which is the bulk of the junk in any scraped list. It cannot tell you that a particular person's mailbox is full or was deleted. If you need that last step, use this first to cut the list down, then pay a mailbox-level verifier for what remains.

Pricing — what you pay per email

This Actor uses pay-per-event pricing: no monthly rental, you pay for the results you get. Prices per 1,000 results by Apify plan:

Event	Free plan	Bronze	Silver	Gold+
email — One email address checked: syntax, domain, MX, disposable and role checks	$0.40	$0.36	$0.34	$0.32

There is also a small start fee of $0.00005 per GB of memory ($0.00005 per run at the default 1 GB). Platform compute is included in the price — you are not billed separately for run time. Set a maximum total charge on the run if you want a hard cap, and use the input limits to control how much is fetched. The current prices are always on the Pricing tab.

Tips

• Start with a small maxResults (say 20) to check the output, then raise it — you only pay per result.
• Rows the Actor cannot read are logged and skipped, never charged — check the run log if a count looks low.

Automate & schedule

Run this Actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it on a cron to keep your data fresh.
• Webhooks — trigger downstream actions the moment a run finishes.

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });
const run = await client.actor('tindacloud/email-verifier').call({
    "emails": [
        "john@stripe.com",
        "info@gmail.com",
        "test@mailinator.com",
        "someone@gmial.com"
    ],
    "datasetEmailField": "email",
    "maxResults": 100000
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} records`);

Python

from apify_client import ApifyClient

client = ApifyClient("MY_APIFY_TOKEN")
run = client.actor("tindacloud/email-verifier").call(run_input={
    "emails": [
        "john@stripe.com",
        "info@gmail.com",
        "test@mailinator.com",
        "someone@gmial.com"
    ],
    "datasetEmailField": "email",
    "maxResults": 100000
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

cURL — run and get the results in one request:

curl -X POST "https://api.apify.com/v2/acts/tindacloud~email-verifier/run-sync-get-dataset-items?token=MY_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"emails": ["john@stripe.com", "info@gmail.com", "test@mailinator.com", "someone@gmial.com"], "datasetEmailField": "email", "maxResults": 100000}'

Integrate with any app

Connect the dataset to thousands of apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new records straight into your CRM or sheet.
• n8n — self-hosted workflows.
• Slack — get notified when a run finishes or finds something new.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.
• Webhooks — call your own endpoint when a run succeeds or fails.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this Actor from Claude, ChatGPT, Cursor or any agent framework through the Apify MCP server — ask your assistant to "check this list of 300 addresses and tell me which ones are safe to send to" and let it run this Actor for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This Actor is agent-ready — AI agents can discover it, run it and pay for it on their own. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic payments:

• x402 — an open, HTTP-native payment protocol. Agents pay in USDC through the Apify MCP server — no Apify account needed.
• Skyfire — agent-to-service payments with pre-funded Skyfire tokens.

Building an AI agent, MCP tool or data pipeline? This Actor is ready to plug in and pay as it goes.

Ready-made examples

Open one, change the fields, press Start — nothing to configure:

• Clean an email list before sending
• Remove disposable and role emails from a list
• Verify email list in bulk
• Verify emails from another scraper run

Frequently asked questions

Do I need an API key or a login?

No. Paste your input, press Start. There is nothing to connect and no account on the target site to create.

How do I export the results?

Every run produces a dataset you can download as JSON, CSV, Excel, XML or HTML, or read through the Apify API from your own code. You can also connect it to Make, Zapier or n8n.

Can I run this on a schedule?

Yes. Apify schedules run it every hour, day or week without you being there. Each run is independent, so a schedule gives you a fresh snapshot every time.

Can I call it from Python or JavaScript?

Yes — the Apify API runs any Actor and returns the dataset, and the official Python and JavaScript clients wrap it in a few lines. AI agents can call it too, through Apify's MCP server.

What does it cost?

You pay per result, not per hour. Filters are applied before anything is charged, so narrowing the input directly lowers the bill. Pages that cannot be read are reported in the log and never charged.

Is this data public?

Everything collected here is what an email list shows to anyone without logging in. Check the target site's terms and the rules that apply to you before using the data commercially.

Related scrapers

• Website Contact & Email Scraper — find the addresses in the first place
• Domain, DNS & WHOIS Intelligence — check the company behind the domain
• LinkedIn Company Scraper — company size, industry and HQ