# Email Finder & Verifier (`novashieldai/email-finder`) Actor Find corporate email addresses by name and domain. Verify emails via SMTP, detect email patterns, and search domains for public emails. - **URL**: https://apify.com/novashieldai/email-finder.md - **Developed by:** [Ali haydar Karadaş](https://apify.com/novashieldai) (community) - **Categories:** Lead generation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Email Finder & Verifier Find professional email addresses by name and company domain, verify if an email is deliverable, discover all emails on a domain, or detect a company's email pattern. We built this to be the most accurate email finder on the platform, combining pattern generation with real SMTP verification so you know the address actually works. ### What does Email Finder & Verifier do? This actor gives you four modes for different email intelligence needs. **Find mode** takes a person's full name and company domain, then generates email candidates based on common patterns (first.last@, flast@, first_last@, etc.). It tests each candidate against the mail server using SMTP verification and returns the best match with a confidence score. You also get MX records, catch-all detection, and the full list of candidates ranked by confidence. **Verify mode** takes an email address you already have and checks whether it is valid and deliverable. It validates the format, checks DNS/MX records, and performs SMTP handshake verification. You get a clear yes/no on deliverability plus the raw SMTP response. **Domain mode** searches a domain for all discoverable email addresses. It detects the email pattern the company uses, returns any emails it can find, and tells you whether the domain is catch-all (accepts all addresses). **Pattern mode** focuses on detecting the email naming convention for a domain. It returns the most likely pattern (e.g., {first}.{last}@domain.com), a confidence score, and example emails that match. ### What data do you get? - Best-match email address with confidence score (0-100) - SMTP verification status (verified or not) - Detected email pattern for the domain - Sources where the email was found - All email candidates with individual confidence scores - Domain MX records - Catch-all domain detection - Email validity and deliverability check - SMTP server response - Pattern confidence score with example emails ### Who is this for? - **Sales development reps** building prospect lists with verified email addresses - **Recruiters** finding candidate contact information for outreach - **PR professionals** locating journalist and editor emails at media outlets - **Link builders** finding webmaster and editor contacts for outreach campaigns - **B2B marketers** enriching lead lists with accurate, deliverable email addresses ### How to use it 1. Pick your mode: find, verify, domain, or pattern. 2. For find mode, enter the person's full name and company domain. 3. For verify mode, paste the email address you want to check. 4. For domain or pattern mode, enter the company domain. 5. Run it and get your results with verification status. ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | mode | string | find | Operation mode: find, verify, domain, or pattern | | name | string | - | Full name (e.g., "John Smith"). Required for find mode | | domain | string | - | Company domain (e.g., "tesla.com"). Required for find, domain, and pattern modes | | email | string | - | Email address to verify. Required for verify mode | ### Sample output ```json { "name": "John Smith", "domain": "tesla.com", "email": "john.smith@tesla.com", "confidence": 92, "verified": true, "pattern": "{first}.{last}", "sources": ["pattern_match", "smtp_verified"], "candidates": [ { "email": "john.smith@tesla.com", "pattern": "{first}.{last}", "confidence": 92, "verified": true, "source": "smtp_verified" }, { "email": "jsmith@tesla.com", "pattern": "{f}{last}", "confidence": 65, "verified": false, "source": "pattern_match" } ], "mx_records": ["mx1.tesla.com", "mx2.tesla.com"], "is_catch_all": false } ```` ### How much does it cost? This actor costs **$0.010 per result** (per email lookup or verification). 1,000 lookups cost $10. Every Apify account includes $5 in free monthly credits, so you can run 500 email lookups for free to test it out. ### Common questions **What does "catch-all" mean?** A catch-all domain accepts emails sent to any address at that domain, whether or not the mailbox exists. When a domain is catch-all, SMTP verification cannot confirm if a specific address is real, so confidence scores will be lower. **How accurate is the email finding?** Accuracy depends on the company. For domains with standard naming patterns (first.last, flast, etc.) and no catch-all, accuracy is typically above 90%. Catch-all domains and unusual patterns reduce confidence. **Can I do bulk lookups?** Yes. Pass multiple name-domain pairs through the Apify API and process them programmatically. Each lookup counts as one result. ### Contact & Custom Solutions Need a custom scraper, higher volume, or a specific integration? We're here to help. If anything isn't working right or you need support, don't hesitate to reach out. - Telegram: [t.me/novashield\_dev](https://t.me/novashield_dev) - Email: novashield.dev@gmail.com # Actor input Schema ## `mode` (type: `string`): Mode ## `name` (type: `string`): Full Name ## `domain` (type: `string`): Company Domain ## `email` (type: `string`): Email to Verify ## Actor input object example ```json { "mode": "find", "name": "John Smith", "domain": "tesla.com" } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "name": "John Smith", "domain": "tesla.com" }; // Run the Actor and wait for it to finish const run = await client.actor("novashieldai/email-finder").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "name": "John Smith", "domain": "tesla.com", } # Run the Actor and wait for it to finish run = client.actor("novashieldai/email-finder").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "name": "John Smith", "domain": "tesla.com" }' | apify call novashieldai/email-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=novashieldai/email-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Email Finder & Verifier", "description": "Find corporate email addresses by name and domain. Verify emails via SMTP, detect email patterns, and search domains for public emails.", "version": "1.0", "x-build-id": "mJ09QcQoaowZICXQh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/novashieldai~email-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-novashieldai-email-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/novashieldai~email-finder/runs": { "post": { "operationId": "runs-sync-novashieldai-email-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/novashieldai~email-finder/run-sync": { "post": { "operationId": "run-sync-novashieldai-email-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Mode", "enum": [ "find", "verify", "domain", "pattern" ], "type": "string", "description": "Mode", "default": "find" }, "name": { "title": "Full Name", "type": "string", "description": "Full Name" }, "domain": { "title": "Company Domain", "type": "string", "description": "Company Domain" }, "email": { "title": "Email to Verify", "type": "string", "description": "Email to Verify" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```