# Email Verifier & Finder - Validate + Find Emails (`piposlab/email-verifier-finder`) Actor Verify email deliverability (syntax, MX, role, disposable) and find likely emails from a name and domain. Bulk, fast, no API key. - **URL**: https://apify.com/piposlab/email-verifier-finder.md - **Developed by:** [Alejandro Bufarini](https://apify.com/piposlab) (community) - **Categories:** Lead generation, Developer tools - **Stats:** 3 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 Verifier & Finder - Validate + Find Emails Two jobs in one actor, with no API key: 1. **Verify** a list of emails - checks syntax, looks up the domain's MX records, and flags role accounts (info@, sales@) and disposable domains. Returns a clear status: `valid`, `risky`, or `invalid`, with the reason. 2. **Find** likely emails from a person's name and company domain - generates and ranks the common patterns (`jane.doe@`, `jdoe@`, `jane@`...) and confirms the domain accepts mail. 3. **Discover** published emails on a company's website (homepage, /contact, /about). ### Modes & input | Mode | Input | Returns | |------|-------|---------| | `verify` | `emails: ["a@x.com", ...]` | status, syntaxValid, mxFound, isRoleAccount, isDisposable, reason, confidence | | `find` | `people: [{fullName, domain}]` | bestGuess, ranked candidates, mxFound | | `discover` | `domains: ["x.com", ...]` | emailsFound[], count | ### Output (verify example) ```json { "email": "jane.doe@example.com", "status": "valid", "syntaxValid": true, "domain": "example.com", "mxFound": true, "mxHost": "aspmx.l.google.com", "isRoleAccount": false, "isDisposable": false, "confidence": "high", "reason": "mx_ok" } ```` ### How verification works (honest) This actor validates at the **DNS / MX + heuristic** level: syntax, whether the domain can receive mail, and whether the address is a role or disposable account. It does **not** open an SMTP mailbox handshake (outbound port 25 is blocked on cloud infrastructure, and aggressive SMTP probing gets sender IPs blacklisted). That makes it fast, reliable, and safe for bulk lists. Treat `valid` as "deliverable domain, well-formed address", not "mailbox confirmed to exist". Clean for lead-gen pipelines: feed it the output of a scraper and get a deduplicated, status-tagged email list. # Actor input Schema ## `mode` (type: `string`): What to do. ## `emails` (type: `array`): List of email addresses to validate. ## `people` (type: `array`): Objects like {"fullName":"Jane Doe","domain":"example.com"} to generate likely emails for. ## `domains` (type: `array`): Domains to scan for published contact emails (homepage, /contact, /about). ## `maxItems` (type: `integer`): Cap on records processed. ## Actor input object example ```json { "mode": "verify", "emails": [ "jane.doe@example.com" ], "people": [ { "fullName": "Jane Doe", "domain": "example.com" } ], "maxItems": 1000 } ``` # 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 = { "emails": [ "jane.doe@example.com" ], "people": [ { "fullName": "Jane Doe", "domain": "example.com" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("piposlab/email-verifier-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "emails": ["jane.doe@example.com"], "people": [{ "fullName": "Jane Doe", "domain": "example.com", }], } # Run the Actor and wait for it to finish run = client.actor("piposlab/email-verifier-finder").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "emails": [ "jane.doe@example.com" ], "people": [ { "fullName": "Jane Doe", "domain": "example.com" } ] }' | apify call piposlab/email-verifier-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=piposlab/email-verifier-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Email Verifier & Finder - Validate + Find Emails", "description": "Verify email deliverability (syntax, MX, role, disposable) and find likely emails from a name and domain. Bulk, fast, no API key.", "version": "0.1", "x-build-id": "VgcczwH4T0OAr0h5V" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/piposlab~email-verifier-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-piposlab-email-verifier-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/piposlab~email-verifier-finder/runs": { "post": { "operationId": "runs-sync-piposlab-email-verifier-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/piposlab~email-verifier-finder/run-sync": { "post": { "operationId": "run-sync-piposlab-email-verifier-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", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "verify", "find", "discover" ], "type": "string", "description": "What to do.", "default": "verify" }, "emails": { "title": "Emails to verify (verify mode)", "type": "array", "description": "List of email addresses to validate.", "items": { "type": "string" } }, "people": { "title": "People (find mode)", "type": "array", "description": "Objects like {\"fullName\":\"Jane Doe\",\"domain\":\"example.com\"} to generate likely emails for." }, "domains": { "title": "Domains (discover mode)", "type": "array", "description": "Domains to scan for published contact emails (homepage, /contact, /about).", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Cap on records processed.", "default": 1000 } } }, "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 } } } } } } } } } } ```