Email Finder

Find verified business email addresses for any person given their name and company domain. Waterfall verification across website scraping, GitHub commits, and Gravatar.

📧 What does Email Finder do?

Email Finder takes a person's name and company domain and returns their most likely business email address. It uses a waterfall approach across multiple verification methods:

🔹 Website Scraping — Fetches the company website (homepage, /contact, /about, /team) and extracts matching emails 🔹 Pattern Detection — Analyzes found emails to detect the company's email pattern, then predicts the target person's email 🔹 GitHub Discovery — Searches public commit history for matching email addresses (great for tech companies) 🔹 Gravatar Check — Verifies if candidate emails have Gravatar profiles (indicating active use) 🔹 Pattern Generation — Generates 11 common email patterns (first.last@, flast@, first@, etc.) as fallback

❓ Why use Email Finder?

🔹 No API keys needed — Works entirely with free, public verification methods 🔹 Waterfall approach — Multiple sources increase find rate beyond any single method 🔹 Website-verified — Finds actual emails published on company websites 🔹 Pattern intelligence — Learns the company's email pattern from found emails, then predicts for the target person 🔹 Transparent results — Shows all candidates, their patterns, and verification status 🔹 Bulk processing — Find emails for hundreds of people in a single run

💡 Use cases

🔹 Sales prospecting — Find decision-maker emails for cold outreach 🔹 Recruiting — Reach candidates directly at their work email 🔹 PR & media — Contact journalists and editors at their publication 🔹 Link building — Find webmaster emails for SEO outreach 🔹 Business development — Reach potential partners at target companies 🔹 Research — Connect with experts and thought leaders

📊 Sample output

Email result

Field	Example
email	john.smith@acme.com
confidence	high
firstName	John
lastName	Smith
domain	acme.com
isCatchAll	false
hasMx	true
sources	smtp, github

Confidence levels

Level	Meaning
high	Found on the company website — confirmed real email
medium	Confirmed via Gravatar, found in GitHub commits, or predicted from detected company pattern
low	Pattern-generated based on common email conventions (first.last@, etc.)

💰 How much does it cost to find business emails?

Event	Price
Start (per run)	$0.005
Person searched	$0.005

Free plan estimate: ~40 email lookups per month on the Apify Free plan.

🔢 How to find business emails

1. Go to the Email Finder page on Apify
2. Add people with first name, last name, and company domain
3. Enable verification methods (SMTP, GitHub, Gravatar)
4. Click "Start" and download results as JSON, CSV, or Excel
5. Use the "confidence" field to prioritize outreach

📥 Input parameters

Parameter	Type	Description
people	array	List of people with firstName, lastName, domain
checkWebsite	boolean	Scrape company website for emails (default: true)
checkGitHub	boolean	Search GitHub commits for email (default: true)
checkGravatar	boolean	Check Gravatar profiles (default: true)
githubToken	string	Optional GitHub token for higher rate limits

Person object

Field	Type	Required	Description
firstName	string	Yes	Person's first name
lastName	string	Yes	Person's last name
domain	string	Yes	Company domain (e.g., "acme.com")
company	string	No	Company name for display
linkedinUrl	string	No	LinkedIn URL for context

📤 Output fields

firstName, lastName, domain, company, linkedinUrl, email, confidence, candidates[], sources[], isCatchAll, hasMx, scrapedAt

Candidate object

email, pattern, status (verified/likely/unverified/invalid), source

💡 Tips

🔹 Start small — Test with 1-2 people first to see the output format before bulk runs. 🔹 Check confidence — "high" means found on website. "medium" means confirmed via Gravatar/GitHub. "low" means pattern-generated only. 🔹 GitHub token — For bulk lookups, add a GitHub personal access token (free) to avoid rate limiting. 🔹 GitHub works best for tech — Engineers, developers, and open-source contributors often have their work email in GitHub commits. 🔹 Common patterns — first.last@domain.com is the most common business email pattern (~60% of companies), followed by flast@ (~15%) and first@ (~10%). 🔹 Multiple people, same company — The actor caches website results per domain, so looking up multiple people at the same company is efficient.

Integrations

Connect Email Finder with your sales and outreach tools:

• Google Sheets — Export found emails directly to a shared prospecting spreadsheet
• Zapier — Trigger email outreach sequences when new contacts are found
• Make — Build pipelines: find emails, verify with Email Enrichment, then push to your CRM
• Slack — Get notified when a batch email search completes
• Webhooks — Send results to your own API for custom processing

💻 API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('automation-lab/email-finder').call({
    people: [
        { firstName: 'John', lastName: 'Smith', domain: 'acme.com' },
        { firstName: 'Jane', lastName: 'Doe', domain: 'startup.io' },
    ],
    verifyEmails: true,
    checkGitHub: true,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_TOKEN')
run = client.actor('automation-lab/email-finder').call(run_input={
    'people': [
        {'firstName': 'John', 'lastName': 'Smith', 'domain': 'acme.com'},
        {'firstName': 'Jane', 'lastName': 'Doe', 'domain': 'startup.io'},
    ],
    'verifyEmails': True,
    'checkGitHub': True,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

cURL

curl "https://api.apify.com/v2/acts/automation-lab~email-finder/runs" \
  -X POST -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -d '{"people": [{"firstName": "John", "lastName": "Smith", "domain": "acme.com"}]}'

⚖️ Legality

Email Finder uses publicly available data sources: company websites (public pages), DNS MX record lookups, public GitHub commit history, and Gravatar's public API. No private data is accessed. Email addresses are found on public web pages or generated from common patterns. Always comply with applicable email regulations (CAN-SPAM, GDPR) when using found emails for outreach.

Use with AI agents via MCP

Email Finder is available as a tool for AI assistants that support the Model Context Protocol (MCP).

Setup for Claude Code

claude mcp add --transport http apify \
  "https://mcp.apify.com?tools=automation-lab/email-finder"

Setup for Claude Desktop, Cursor, or VS Code

Add this to your MCP config file:

{
    "mcpServers": {
        "apify-email-finder": {
            "url": "https://mcp.apify.com?tools=automation-lab/email-finder"
        }
    }
}

Example prompts

Once connected, try asking your AI assistant:

• "Find the email address for John Smith at Acme Corp"
• "Search for contact emails at these 10 companies"

Learn more in the Apify MCP documentation.

FAQ

Q: How accurate is the email verification? A: Emails found on the company website (high confidence) are 95%+ accurate. Gravatar-confirmed emails are very reliable. Pattern-only predictions (low confidence) have ~60-70% accuracy depending on how common the company's email format is.

Q: Why do I need a GitHub token? A: GitHub limits unauthenticated API requests to 10/minute. With a personal access token (free at github.com/settings/tokens), you get 30 requests/minute. Essential for bulk lookups.

Q: Does it work for Gmail/Yahoo/personal emails? A: No. It's designed for business emails at company domains. Gmail, Yahoo, and Outlook personal accounts don't follow predictable patterns.

Q: How many emails can I find per run? A: The actor processes people in sequence, checking multiple sources. Expect ~50-100 people per minute. For large lists, consider adding a GitHub token for better results.

Q: The actor didn't find an email for a person I know works at that company. Why? A: The actor relies on public data -- company website pages, GitHub commits, and Gravatar. If the person's email isn't published on any of these sources, the actor falls back to pattern generation (low confidence). Try providing the exact company domain (not a parent company domain) for better results.

Q: Can I combine this with other Apify actors? A: Yes. A common workflow is: use Google Maps Lead Finder to find businesses, then pass company domains and contact names to Email Finder to get verified emails. Chain them with Make or Zapier.

Q: GitHub search isn't finding results. What can I do? A: GitHub limits unauthenticated API requests to 10/minute. Add a free GitHub personal access token (from github.com/settings/tokens) in the githubToken field to increase the limit to 30/minute. Also note that GitHub works best for tech companies where employees make public commits.

Other lead generation tools

🔹 Email Enrichment — Enrich email addresses with company and contact data 🔹 Website Contact Finder — Find emails, phones, and social links from any website 🔹 Social Media Profile Finder — Find social profiles for any website 🔹 Google Maps Lead Finder — Generate leads from Google Maps 🔹 Multi-Source Lead Enrichment — Enrich leads from multiple data sources