# B2B Email Finder (`dxbear/b2b-email-finder`) Actor 🔍 Find verified B2B emails using names and company domains. Get valid leads for sales outreach, recruiting, and email marketing campaigns. 📧🏢 - **URL**: https://apify.com/dxbear/b2b-email-finder.md - **Developed by:** [Dxbear](https://apify.com/dxbear) (community) - **Categories:** Lead generation, Jobs, Automation - **Stats:** 3 total users, 3 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $8.00 / 1,000 email founds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## 📧 B2B Email Finder > Find and validate professional email addresses for any prospect — just provide a name and company domain. --- ### 🔍 Overview **B2B Email Finder** is an Apify Actor designed to find and verify professional email addresses specifically for B2B outreach. By inputting a prospect's first name, last name, and company domain, this actor works to find and confirm their email address. It performs various checks, including format validation, disposable email detection, webmail identification, and live SMTP verification. No more guessing `john.doe@company.com` or wasting time on bounced outreach. This actor gives you a validated, deliverable email address. #### What It Can Do - ✅ Generate professional email address suggestions based on popular naming patterns - ✅ Validate the format and structure of email addresses - ✅ Identify disposable (temporary) email providers - ✅ Recognize webmail addresses like Gmail, Yahoo, Outlook, and others - ✅ Conduct live SMTP verification to ensure the mailbox is real - ✅ Flag any gibberish or auto-generated-looking addresses --- ### 🚀 How to Use It **Step 1 — Sign up for Apify** Go to [apify.com](https://apify.com/) and create a free account. New users get **$5 in free credits** — enough to validate hundreds of emails right away, with no credit card required. **Step 2 — Open the Actor** Find **B2B Email Finder** in the Apify Store and click **Try for free**. **Step 3 — Fill in the input** Provide the prospect's first name, last name, and their company's domain (e.g., `apify.com`, not the full URL). **Step 4 — Run and collect results** Click **Start** and within seconds you'll see validated email results in the output dataset. You can download results as JSON or CSV, or connect them directly to your CRM or workflow. --- ### 📥 Input Example ```json { "firstName": "Jane", "lastName": "Doe", "companyDomain": "apify.com" } ```` | Field | Type | Required | Description | |-----------------|--------|----------|--------------------------------------------------| | `firstName` | string | ✅ | Prospect's first name | | `lastName` | string | ✅ | Prospect's last name | | `companyDomain` | string | ✅ | Company website domain (e.g., `apify.com`) | *** ### 📤 Output Example ```json { "email": "jane.doe@apify.com", "smtp_status": "valid", "is_valid_format": true, "is_disposable": false, "is_webmail": false, "is_gibberish": false } ``` | Field | Type | Description | |------------------|---------|--------------------------------------------------------------------| | `email` | string | The email address that was validated | | `smtp_status` | string | SMTP check result: `valid`, `invalid`, or `unknown` | | `is_valid_format`| boolean | Whether the email has a valid format | | `is_disposable` | boolean | Whether it belongs to a disposable/throwaway provider | | `is_webmail` | boolean | Whether it's a webmail address (Gmail, Yahoo, etc.) | | `is_gibberish` | boolean | Whether the address looks auto-generated or like gibberish | *** ### 🤖 How to Integrate It in an AI Agent Apify makes it easy to plug this actor directly into your AI agent workflows — no custom backend needed. #### Option 1 — Apify MCP Server *(for Claude, GPT, and other AI agents)* Apify provides a native MCP (Model Context Protocol) server that lets AI agents like Claude call Apify actors as tools in real time. 1. Go to your [Apify Console](https://console.apify.com/) → **Integrations** → **MCP Server** 2. Copy your MCP endpoint URL 3. Add it as an MCP tool in your AI agent setup 4. Your agent can now call B2B Email Finder as a live tool — passing a name and domain, and getting back a validated email mid-conversation #### Option 2 — Apify API [Read more about the API documentation](https://docs.apify.com/api/v2) #### Option 3 — Zapier, Make, or n8n *(no-code automation)* Use Apify's native Zapier or Make integrations to trigger the actor from any workflow — for example, when a new lead is added to a spreadsheet, automatically find and validate their email. *** ### 💰 Pricing | Volume | Cost | |-------------------------|------------| | 1,000 emails validated | **$8.00** | | Per email | ~$0.008 | > **Note:** The above is the actor usage cost. Apify platform compute costs apply separately based on your plan. New users receive **$5 in free credit** upon signup — no credit card required. For high-volume use (10,000+ emails/month), consider the Apify Scale or Business plan for the best cost efficiency. *** ### 👥 Who Can Use This Actor? This actor is built for anyone who does professional B2B outreach or lead research: - **Sales Development Representatives (SDRs)** — Build targeted prospect lists with verified contact emails - **Growth hackers & marketers** — Fuel cold email campaigns with deliverable addresses - **Recruiters** — Reach hiring managers and candidates at their work emails - **Founders & entrepreneurs** — Contact potential partners, investors, or clients directly - **Data engineers & analysts** — Enrich CRM or lead database records with validated email fields - **AI agent builders** — Give your sales or research agent the ability to find contact info autonomously *** ### ✅ What Can You Do With This Actor? Here are common real-world use cases: **Cold outreach campaigns** — Validate a list of prospects before sending, so your bounce rate stays low and your sender reputation stays healthy. **CRM enrichment** — Have a name and company but missing the email? Run it through this actor to fill the gap automatically. **Lead generation pipelines** — Pair this actor with a LinkedIn scraper or company list to build full contact profiles at scale. **AI sales agents** — Let your AI agent autonomously research a prospect and find their verified work email before drafting an outreach message. **Recruitment outreach** — Find direct work emails for hiring managers or candidates instead of relying on generic contact forms. **Account-based marketing (ABM)** — Identify and validate emails for specific decision-makers at your target accounts. **Data cleaning** — Pass existing email lists through the validator to flag invalid, disposable, or webmail addresses before your next campaign. *** *Built on [Apify](https://apify.com/) — the platform for web scraping and automation at scale.* # Actor input Schema ## `firstName` (type: `string`): The first name of the prospect (e.g., Jane). ## `lastName` (type: `string`): The last name of the prospect (e.g., Doe). ## `companyDomain` (type: `string`): The website domain of the target company (e.g., apify.com). ## Actor input object example ```json { "firstName": "Saurav", "lastName": "Jain", "companyDomain": "apify.com" } ``` # Actor output Schema ## `results` (type: `string`): Found email addresses with validation details. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("dxbear/b2b-email-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 = {} # Run the Actor and wait for it to finish run = client.actor("dxbear/b2b-email-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 '{}' | apify call dxbear/b2b-email-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dxbear/b2b-email-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "B2B Email Finder", "description": "🔍 Find verified B2B emails using names and company domains. Get valid leads for sales outreach, recruiting, and email marketing campaigns. 📧🏢", "version": "1.0", "x-build-id": "dfVpYYFkB2Mjaygv5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dxbear~b2b-email-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dxbear-b2b-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dxbear~b2b-email-finder/runs": { "post": { "operationId": "runs-sync-dxbear-b2b-email-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dxbear~b2b-email-finder/run-sync": { "post": { "operationId": "run-sync-dxbear-b2b-email-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "firstName", "lastName", "companyDomain" ], "properties": { "firstName": { "title": "First Name", "type": "string", "description": "The first name of the prospect (e.g., Jane).", "default": "Saurav" }, "lastName": { "title": "Last Name", "type": "string", "description": "The last name of the prospect (e.g., Doe).", "default": "Jain" }, "companyDomain": { "title": "Company Domain", "type": "string", "description": "The website domain of the target company (e.g., apify.com).", "default": "apify.com" } } }, "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 } } } } } } } } } } ```