# Email Extractor Pro (`knotless_cadence/email-extractor-pro`) Actor Extract emails from any website or URL list. 12+ runs for lead gen and outreach. CSV/JSON. Custom email scraper built in 48h, $100 pilot. Email: spinov001@gmail.com • Tips: t.me/scraping\_ai - **URL**: https://apify.com/knotless\_cadence/email-extractor-pro.md - **Developed by:** [Alex](https://apify.com/knotless_cadence) (community) - **Categories:** Lead generation, Marketing, Open source - **Stats:** 3 total users, 0 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 Extractor Extract email addresses, phone numbers, and social media links from any website. Automatically crawls multiple pages, follows internal links, and prioritizes contact/about pages. Get clean, deduplicated results ready for outreach. ### Features - **Deep crawling** — follows internal links up to 3 levels deep to find emails hidden on subpages - **Smart page prioritization** — automatically prioritizes contact, about, team, and legal pages where emails are most likely found - **Phone extraction** — extracts phone numbers from tel: links and page text (international formats supported) - **7 social platforms** — detects LinkedIn, Twitter/X, Facebook, Instagram, YouTube, GitHub, and TikTok links - **Spam filtering** — automatically filters out junk emails (noreply, test domains, image files) - **mailto: detection** — extracts verified emails from mailto: links (highest accuracy) - **Bulk processing** — scan hundreds of websites in a single run with 10 concurrent crawlers ### Output Example ```json { "email": "contact@example.com", "source": "https://example.com/contact", "domain": "example.com", "fromMailto": true, "phones": ["+1 (555) 123-4567", "+44 20 7946 0958"], "socialLinks": [ { "platform": "linkedin", "url": "https://linkedin.com/company/example" }, { "platform": "twitter", "url": "https://twitter.com/example" } ], "scrapedAt": "2026-03-18T12:00:00.000Z" } ```` ### Use Cases - **Lead generation** — build email lists from company websites for B2B outreach campaigns - **Sales prospecting** — find decision-maker contact info across hundreds of target company sites - **PR and link building** — collect journalist and blogger emails for outreach - **Recruitment** — extract contact details from agency and freelancer websites - **Data enrichment** — add email, phone, and social media data to your existing company database ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `urls` | Array | `[]` | List of website URLs to scan for emails | | `maxPagesPerDomain` | Number | `20` | Maximum pages to crawl per domain | | `maxDepth` | Number | `2` | How many link levels deep to crawl (0-3) | | `includePhones` | Boolean | `true` | Whether to extract phone numbers | | `includeSocialLinks` | Boolean | `true` | Whether to extract social media profile links | | `deduplicateEmails` | Boolean | `true` | Remove duplicate email addresses | ### Cost Estimation - \~$0.50 per 50 websites scanned (20 pages each) - \~$1.00 per 100 websites with phones and social links - Free tier: up to 20 websites with Apify free plan ### FAQ **Q: How many emails can I expect per website?** A: It varies widely. A typical business website yields 1-5 unique email addresses. Larger sites with team pages can return 10-20+. The scraper crawls up to 20 pages per domain by default to maximize discovery. **Q: Does it filter out generic/spam emails?** A: Yes. The scraper automatically filters out noreply@, test domains, image file extensions, and other junk patterns. Only real, contactable email addresses are returned. **Q: Can I extract emails from password-protected pages?** A: No. The scraper only accesses publicly available pages. It does not log in or bypass authentication. # Actor input Schema ## `urls` (type: `array`): List of website URLs to extract contacts from ## `maxPagesPerDomain` (type: `integer`): How many pages to crawl per website ## `maxDepth` (type: `integer`): How deep to follow links (0 = only provided URLs) ## `includePhones` (type: `boolean`): Whether to extract phone numbers found on the pages ## `includeSocialLinks` (type: `boolean`): Whether to extract links to social media profiles (Facebook, Twitter, LinkedIn, etc.) ## `deduplicateEmails` (type: `boolean`): Whether to remove duplicate email addresses from the results ## Actor input object example ```json { "urls": [ "https://example.com" ], "maxPagesPerDomain": 20, "maxDepth": 2, "includePhones": true, "includeSocialLinks": true, "deduplicateEmails": true } ``` # 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 = { "urls": [ "https://example.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("knotless_cadence/email-extractor-pro").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 = { "urls": ["https://example.com"] } # Run the Actor and wait for it to finish run = client.actor("knotless_cadence/email-extractor-pro").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 '{ "urls": [ "https://example.com" ] }' | apify call knotless_cadence/email-extractor-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=knotless_cadence/email-extractor-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Email Extractor Pro", "description": "Extract emails from any website or URL list. 12+ runs for lead gen and outreach. CSV/JSON. Custom email scraper built in 48h, $100 pilot. Email: spinov001@gmail.com • Tips: t.me/scraping_ai", "version": "1.0", "x-build-id": "vMJ4b7DMXbSkb9aJT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/knotless_cadence~email-extractor-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-knotless_cadence-email-extractor-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/knotless_cadence~email-extractor-pro/runs": { "post": { "operationId": "runs-sync-knotless_cadence-email-extractor-pro", "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/knotless_cadence~email-extractor-pro/run-sync": { "post": { "operationId": "run-sync-knotless_cadence-email-extractor-pro", "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": [ "urls" ], "properties": { "urls": { "title": "Website URLs", "type": "array", "description": "List of website URLs to extract contacts from", "default": [], "items": { "type": "string" } }, "maxPagesPerDomain": { "title": "Max Pages Per Domain", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many pages to crawl per website", "default": 20 }, "maxDepth": { "title": "Crawl Depth", "minimum": 0, "maximum": 5, "type": "integer", "description": "How deep to follow links (0 = only provided URLs)", "default": 2 }, "includePhones": { "title": "Include Phone Numbers", "type": "boolean", "description": "Whether to extract phone numbers found on the pages", "default": true }, "includeSocialLinks": { "title": "Include Social Media Links", "type": "boolean", "description": "Whether to extract links to social media profiles (Facebook, Twitter, LinkedIn, etc.)", "default": true }, "deduplicateEmails": { "title": "Remove Duplicate Emails", "type": "boolean", "description": "Whether to remove duplicate email addresses from the results", "default": true } } }, "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 } } } } } } } } } } ```