Email Verifier & Validator (DNS): Bulk, MX, Disposable

Email Verifier & Validator (DNS): Bulk, MX, Disposable

Paste a list of emails, or pick an Apify dataset from a leads or contact scraper. For every email the Actor checks:

• Syntax: a real address format, with mailto: and <...> cleaned off.
• Mail servers: the domain exists and has MX records (or at least an address record). Domains with a "null MX" accept no mail.
• Disposable domains: about 10,000 throwaway email domains (mailinator, yopmail and others), with their subdomains.
• Typos: gmial.com, hotmial.com, gmail.con and more, with a fixed address in didYouMean.
• Role accounts: info@, sales@, support@ and similar.
• Free providers: Gmail, Yahoo, Outlook, iCloud and about 60 more, so you can split business and personal emails.

Each email gets a status: valid, risky, invalid or unknown, with the reasons.

$0.30 per 1,000 emails. No API key. It never sends an email and never opens an SMTP connection, so it is fast, it does not time out on slow mail servers, and it cannot hurt your sender reputation. It works with limited permissions: it reads only the datasets you pick.

How to use

1. Open the Actor in the Apify Console and go to the Input tab.
2. Paste emails into Emails, one per line. Or pick a dataset in Datasets with emails and type its email field in Email field in the dataset.
3. Click Start.
4. When the run ends, open the Output tab. Download the results as CSV, Excel or JSON, or read them through the API.

The prefilled input checks 6 sample emails (a good one, a typo, a disposable one, a domain that takes no mail, and a broken address), so a one-click run shows every status.

What can you do with it?

• Clean a lead list before a campaign: drop invalid emails and fix typos, so fewer emails bounce.
• Check scraper output: run it after a contact or leads scraper as an integration, with {{resource.defaultDatasetId}}. Fields that hold a list of emails, like emails, give one row per email, with the original item.
• Stop fake signups: flag disposable and mistyped emails in a form export.
• Split B2B and B2C: use isFreeProvider and isRoleAccount to sort leads.
• AI agents: call the Actor as a tool (Apify API or Apify MCP server) before an agent writes to a list of people.

Input examples

Two inputs you can paste into the JSON tab and run as they are. Results are from real runs on Oct 27, 2026. No email is sent to any of these addresses.

1. Every status in one run. About 1 second. Results: info@apify.com valid (role account), someone@gmail.con invalid with didYouMean someone@gmail.com, help@crawlee.dev risky (role account, no MX record), sam@guerrillamail.com risky (disposable), and the made-up domain invalid (domain not found).

{
  "emails": [
    "info@apify.com",
    "someone@gmail.con",
    "help@crawlee.dev",
    "sam@guerrillamail.com",
    "jane@nonexistent-domain-brasspage-test.com"
  ],
  "outputFilter": "all"
}

2. Drop the invalid ones. The same 5 emails with "outputFilter": "notInvalid". The dataset keeps 3 rows (1 valid, 2 risky). All 5 still count toward the price.

{
  "emails": [
    "info@apify.com",
    "someone@gmail.con",
    "help@crawlee.dev",
    "sam@guerrillamail.com",
    "jane@nonexistent-domain-brasspage-test.com"
  ],
  "outputFilter": "notInvalid"
}

From a dataset:

{
  "datasetIds": ["<dataset ID>"],
  "emailField": "emails",
  "outputFilter": "notInvalid"
}

Output example

{
  "email": "jane.doe@gmial.com",
  "normalized": "jane.doe@gmial.com",
  "status": "risky",
  "reasons": ["possible_typo", "disposable_domain"],
  "domain": "gmial.com",
  "hasMx": false,
  "mxHosts": [],
  "isDisposable": true,
  "isRoleAccount": false,
  "isFreeProvider": false,
  "didYouMean": "jane.doe@gmail.com"
}

Rows from a dataset also hold the original item in item. The OUTPUT record holds a summary: emails checked, counts per status, rows written, and notes.

Statuses and reasons

Status	Meaning	Reasons
valid	Good format, the domain takes mail, no warning signs	can still list role_account
risky	Mail may arrive, but it is a bad bet	disposable_domain, possible_typo, no_mx_record (no MX, only an address record)
invalid	Mail cannot arrive	syntax_..., domain_not_found, no_mail_server, domain_accepts_no_mail
unknown	DNS did not answer in time. Run these emails again later	dns_error

Limits

It does not ask the mail server if the mailbox exists (an SMTP check). Big providers like Gmail and Outlook do not answer that question honestly, and SMTP checks from cloud servers are slow and often blocked. So valid means "the address and its domain are fine", not "a person reads this inbox". If you need mailbox checks, run the valid rows through an SMTP verifier after this one, and pay for fewer emails there.

• The Apify free plan checks up to 2,000 emails per run.
• DNS answers time out after 4 seconds (2 tries). An email whose domain does not answer gets unknown.
• Typo fixes come from a fixed list of common providers and TLD slips like .con, so a typo of a small company domain is not caught.

Pricing

• $0.30 per 1,000 emails checked ($0.0003 per email). Duplicates in Emails are checked and charged once.
• A tiny Actor start event (Apify's standard start charge) applies once per run.
• Emails you drop with Rows to keep still count, because they were checked.
• The Apify free plan checks up to 2,000 emails per run.
• Set Max emails to check or a maximum total charge on the run, and the Actor stops before it goes over.
• The prefilled input checks 6 emails, so a one-click run costs about $0.002 (6 x $0.0003), plus the start fee.

FAQ

Does it send email? No. It only makes DNS queries for the domains.

Is the disposable list up to date? It ships with the public disposable-email-domains list (CC0) and is updated with new builds.

Is my data stored? Only in your own run's dataset and key-value store.

What does valid mean? The address is well formed, its domain has mail servers, and there are no warning signs. It does not prove a person reads the inbox (see Limits).

Why did some emails get unknown? DNS for their domain did not answer in time. Run those emails again later.

Related Actors

• Dataset Dedup & Merge: remove duplicate leads by email before you check them.
• Website Contact & Tech Audit: find the emails on a list of websites, then check them here.
• Google Sheets Export & Sync: send the checked emails to a Google Sheet.

Issues and support

Found a bug or need a feature? Open an issue in this Actor's Issues tab. We check it every day and reply there.