# 📧 Email & Phone Extractor (`busy_bumper/email-phone-extractor`) Actor 🔍 Extract emails, phone numbers & social media profiles from any website. Detects LinkedIn, Instagram, Facebook, YouTube, TikTok, Twitter, WhatsApp, Telegram & more. ⚡ Fast, clean results — no setup needed. Just paste a URL and go! 📋 - **URL**: https://apify.com/busy\_bumper/email-phone-extractor.md - **Developed by:** [Kira](https://apify.com/busy_bumper) (community) - **Categories:** Developer tools, E-commerce, Lead generation - **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 results 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 ## 📧 Email & Phone Extractor Crawls any website and extracts all publicly listed contact information — emails, phone numbers, and social media profiles — from multiple pages within the same domain. ### What it extracts - 📧 **Emails** — including Cloudflare-protected addresses (`data-cfemail`) - 📞 **Phone numbers** — confirmed (`tel:` links) and uncertain (text patterns) - 📝 **Description** — auto-generated summary of what the website is about - 💼 LinkedIn profiles - 🐦 Twitter / X handles - 📸 Instagram profiles - 📘 Facebook pages - ▶️ YouTube channels - 🎵 TikTok profiles - 📌 Pinterest profiles - 🎮 Discord servers - 👻 Snapchat profiles - 🧵 Threads profiles - ✈️ Telegram groups - 👥 Reddit pages - 💬 WhatsApp links ### How it works 1. You provide a starting URL and the number of pages to crawl 2. The scraper prioritizes contact-relevant paths (`/contact`, `/directorio`, `/about`, `/staff`, `/pqrs`, etc.) automatically — even if they are not linked from the homepage 3. It detects and decodes **Cloudflare-obfuscated emails** that are invisible in the raw HTML 4. All results are deduplicated and merged into a single JSON output per domain ### Input | Field | Type | Required | Default | Description | |---|---|---|---|---| | `startUrls` | array | ✅ | — | One or more website URLs to scrape | | `maxPagesPerStartUrl` | integer | ❌ | 20 | Max pages to crawl per site (1–200) | ### Output ```json [ { "originalStartUrl": "https://unipaz.edu.co/", "domain": "unipaz.edu.co", "description": "Instituto Universitario de la Paz UNIPAZ, Instituto de Educación Superior del Magdalena Medio. Actualidad, educación y temas de interés para la universidad. Asiste a los diferentes eventos que suceden en nuestra Institución educativa. Visita nuestros canales de comunicación y mantente conectado con la actualidad de la U. En este momento las inscripciones se encuentran cerradas, estar atentos a la proxima convocatorias que inician el próximo 18 de mayo del presente año", "emails": [ "atencionalciudadano@unipaz.edu.co", "bienestar.universitario@unipaz.edu.co", "contabilidad@unipaz.edu.co", "dir.agroindustrial@unipaz.edu.co", "dir.agronomica@unipaz.edu.co", "dir.ambiental@unipaz.edu.co", "dir.centrodeinformacion@unipaz.edu.co", "dir.ciencias@unipaz.edu.co", "dir.cienciassociales@unipaz.edu.co", "dir.investigaciones@unipaz.edu.co", "dir.mvz@unipaz.edu.co", "dir.produccion@unipaz.edu.co", "direccion.administrativa@unipaz.edu.co", "evaluacionycontrol@unipaz.edu.co", "gestion.humana@unipaz.edu.co", "notificacionesjudiciales@unipaz.edu.co", "planeacion@unipaz.edu.co", "rectoria@unipaz.edu.co", "registro@unipaz.edu.co", "secretaria.escuelas@unipaz.edu.co", "secretaria.general@unipaz.edu.co", "servicios.generales@unipaz.edu.co", "sistemas@unipaz.edu.co", "tesoreria@unipaz.edu.co", "ventanillaunica@unipaz.edu.co", "vicerrectoria@unipaz.edu.co" ], "phones": [], "phonesUncertain": [ "1313116729577", "3222703665", "607)6118210", "6118210" ], "linkedIns": [], "twitters": ["https://twitter.com/UNIPAZnoticias"], "instagrams": ["https://www.instagram.com/unipaznoticias"], "facebooks": ["https://www.facebook.com/people/Instituto-Universitario-de-la-Paz/100064522486908/"], "youtubes": [ "https://www.youtube.com/@UNIPAZNoticias", "https://www.youtube.com/channel/UC9EH2zVkgzGZCJWPAw2Dauw" ], "tiktoks": [], "pinterests": [], "discords": [], "snapchats": [], "threads": [], "telegrams": [], "reddits": [], "whatsapps": [], "scrapedUrls": [ "https://unipaz.edu.co/", "https://unipaz.edu.co/directorio", "https://unipaz.edu.co/directorio-institucional", "https://unipaz.edu.co/personal", "https://unipaz.edu.co/equipo" ] } ] ```` Results can be downloaded as **JSON, CSV, Excel, or HTML** from the Apify dataset tab. # Actor input Schema ## `startUrls` (type: `array`): One or more websites to scrape contact details from. ## `maxPagesPerStartUrl` (type: `integer`): Maximum number of pages to crawl per website. ## Actor input object example ```json { "startUrls": [ { "url": "https://apify.com" } ], "maxPagesPerStartUrl": 20 } ``` # 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 = { "startUrls": [ { "url": "https://apify.com" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("busy_bumper/email-phone-extractor").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 = { "startUrls": [{ "url": "https://apify.com" }] } # Run the Actor and wait for it to finish run = client.actor("busy_bumper/email-phone-extractor").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 '{ "startUrls": [ { "url": "https://apify.com" } ] }' | apify call busy_bumper/email-phone-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=busy_bumper/email-phone-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "📧 Email & Phone Extractor", "description": "🔍 Extract emails, phone numbers & social media profiles from any website. Detects LinkedIn, Instagram, Facebook, YouTube, TikTok, Twitter, WhatsApp, Telegram & more. ⚡ Fast, clean results — no setup needed. Just paste a URL and go! 📋", "version": "0.0", "x-build-id": "12nmAlq598BvmzxLH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/busy_bumper~email-phone-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-busy_bumper-email-phone-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/busy_bumper~email-phone-extractor/runs": { "post": { "operationId": "runs-sync-busy_bumper-email-phone-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/busy_bumper~email-phone-extractor/run-sync": { "post": { "operationId": "run-sync-busy_bumper-email-phone-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "One or more websites to scrape contact details from.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxPagesPerStartUrl": { "title": "Max pages per start URL", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of pages to crawl per website.", "default": 20 } } }, "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 } } } } } } } } } } ```