# Doctors Email Scraper (`scraperoka/doctors-email-scraper`) Actor 🩺 Doctors Email Scraper extracts verified doctors’ emails from targeted directories and profiles. Save time on outreach with GDPR-aware workflows. 🚀 Perfect for B2B lead generation, marketing, and recruitment—find the right contacts fast. - **URL**: https://apify.com/scraperoka/doctors-email-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ### Doctors Email Scraper 📬 **Doctors Email Scraper** automates the process of finding healthcare providers in a chosen region and extracting their contact information—especially email addresses—so you can build a targeted outreach list faster. If you’re looking for a **doctors email scraper**, a **doctor email list scraper**, or **find doctor emails** for healthcare campaigns, this tool helps you turn publicly available business listings into structured contact data. Whether you’re a marketer, recruiter, clinic operator, or data analyst, you can use this **healthcare doctors email scraper** to speed up lead research and save hours of manual work. --- ### Why choose Doctors Email Scraper? | Feature | Benefit | | --- | --- | | ✅ All-in-one doctor contact extraction | Extracts business info plus scraped emails, phone numbers, and social media links in one workflow | | ✅ Reliability-focused scraping pipeline | Includes built-in fallbacks and resilient scraping logic for better results at scale | | ✅ Email-focused saving logic | Outputs rows that include email results when available, and can also save non-email businesses depending on your mode | | ✅ Structured dataset output | Saves results with consistent fields like `name`, `website`, `scraped_emails`, `emails_found`, and `scrape_status` | | ✅ Region scaling support | Works across multiple locations, with a clear control over how many businesses to target | | ✅ Proxy configuration support | Lets you provide proxy settings for more stable large-scale runs | --- ### Key features - 🩺 **Healthcare-ready email harvesting**: Designed for extracting emails from doctor and clinic business websites for targeted doctor email outreach. - 🔎 **Location-based doctor email discovery**: Uses your **location(s)** and **search term** to focus the results on the right geography. - 🌐 **Website-first contact extraction**: Pulls contact details from business websites and compiles them into structured results. - 📞 **Phone and social discovery included**: Alongside scraped emails, it captures `scraped_phones` and `scraped_social_media`. - 🛡️ **Resilient, resilience-minded scraping**: Uses concurrency controls and a stop condition to keep runs efficient and robust. - 💾 **Real-time dataset saving**: Pushes results to the dataset as scraping progresses (not only at the end), reducing risk of data loss. - 🧠 **Output deduplication**: Avoids duplicate businesses by tracking `place_id` uniqueness during collection. - ✅ **Email-only mode behavior**: In email-only mode, it stores only businesses with emails found (when applicable) to keep your list clean. --- ### Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Doctors", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `googleMapsSearchTerm` | Yes | The business type or niche to search for email scraping (for example, `dentists`). Prefilled with `Doctors`. | | `googleMapsLocation` | Yes | A list of geographic locations to target (for example, `Miami, Florida` or just `New York`). | | `maxBusinesses` | No | The maximum number of businesses to target for email results (1–1000). The scraper stops when the target is reached. Default is `5`. | | `scrapeMaxBusinessesPerLocation` | No | Controls how `maxBusinesses` is applied across multiple locations. If `true`, it collects up to `maxBusinesses` results per location. If `false`, it combines all locations up to a single total limit. Default is `false`. | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for large-scale scraping. Prefilled so `proxy support` is `true`. | | `proxyConfiguration` • `proxy support` | No | When enabled, uses Apify Proxy for scraping. | *** ### Output The actor saves results to the Apify dataset in a table-friendly JSON structure where each saved row includes business details plus extracted contact fields. Example output row (one email row when an email is found for a business): ```json { "street_address": "123 Example St", "city": "New York", "zip": "10001", "state": "NY", "country_code": "US", "full_address": "123 Example St New York NY 10001 US", "website": "https://exampleclinic.com", "avg_rating": 4.6, "total_reviews": 120, "name": "Example Clinic", "place_id": "ChIJ...", "phone": "+1 555 123 4567", "lat": 40.7128, "long": -74.006, "scraped_emails": [ "contact@exampleclinic.com" ], "scraped_phones": [ "+1 555 987 6543" ], "scraped_social_media": [ "https://www.linkedin.com/company/exampleclinic/" ], "emails_found": 1, "pages_scraped": 3, "scrape_status": "success", "email_found": "contact@exampleclinic.com" } ``` > Note: When an email is found, the actor flattens the output by pushing one dataset row per email using `email_found`. In those flattened rows, the `scraped_emails` array is removed. #### Output Fields | Field | Type | Description | | --- | --- | --- | | `name` | string | Business name (the doctor/clinic listing name). | | `website` | string | Business website URL (used as the target for contact extraction). | | `phone` | string | Phone number from the business listing. | | `full_address` | string | Full address constructed from street address, city, state, zip, and country code. | | `city` | string | City. | | `state` | string | State/region. | | `zip` | string | ZIP/postal code. | | `country_code` | string | Country code. | | `scraped_emails` | array | Emails scraped from the business website (present in non-flattened cases; removed in flattened email rows). | | `scraped_phones` | array | Phone numbers scraped from the business website. | | `scraped_social_media` | array | Social media profile links scraped from the business website. | | `emails_found` | number | Count of scraped emails found for the business. | | `pages_scraped` | number | Number of processed URLs/pages during website scraping. | | `avg_rating` | number | Average rating from the business listing. | | `total_reviews` | number | Total number of reviews from the business listing. | | `lat` | number | Latitude from the listing data. | | `long` | number | Longitude from the listing data. | | `place_id` | string | Unique identifier used to deduplicate businesses during collection. | | `scrape_status` | string | Scraping status (examples include `success`, `failed`, and `no_website`). | | `email_found` | string | The specific email value pushed for that row (used when the actor pushes one row per email). | | `scrape_error` | string | Error details when scraping fails (added when `scrape_status` indicates failure/error). | *** ### How to use Doctors Email Scraper (via Apify Console) 1. **Open Apify Console**\ Go to [console.apify.com](https://console.apify.com) and sign in. 2. **Find the actor listing**\ Search for **Doctors Email Scraper** and open the actor page. 3. **Enter your search term and locations**\ In the **INPUT** section, set: - `googleMapsSearchTerm` (defaults to `Doctors`) - `googleMapsLocation` (one or more city/region strings) 4. **Set your limits**\ Configure `maxBusinesses` to control how many businesses you want with email results.\ If you’re using multiple locations, decide whether to enable `scrapeMaxBusinessesPerLocation`. 5. **(Recommended) Configure proxies for scale**\ In `proxyConfiguration`, enable `proxy support` (recommended for larger batches). 6. **Click Run**\ Start the actor run. You’ll see progress logs as it collects businesses and then scrapes their websites for contact details. 7. **Review the dataset output**\ After completion, open the dataset (from the **OUTPUT** tab). Each row contains the business contact fields plus either the flattened `email_found` (when emails are found) or fields reflecting the scrape status. No coding required—get targeted doctor email outreach data in minutes. 🚀 *** ### Advanced features & SEO optimization - 🧩 **Engineered for doctors email scraper workflows**: Built specifically around doctor and clinic website contact extraction, including a clean path for **dentist email scraper** and **hospital email scraper**-style research. - 🌍 **Targeted doctor email outreach tool setup**: Use **search term** + **location list** to narrow results to the exact geography you care about, helping with **clinic email scraper** and **private practice email scraper** use cases. - 📊 **Verified-like dataset structure for analysis**: The output includes both discovery fields (rating/reviews/place info) and scraped contact fields, making it easier to build a **verified doctors email list** for segmentation. - 💾 **Email-focused list hygiene**: Supports an email-only behavior via its internal email handling logic, which is especially useful for a **bulk doctors email extractor** workflow. *** ### Best use cases - 📈 **Healthcare lead generation**: Build a targeted email list of clinics and providers for outreach campaigns. - 🧠 **Market research**: Compare provider density and contactability across regions using `avg_rating`, `total_reviews`, and contact fields. - 🏥 **Hospital and specialty outreach**: Collect emails for **hospital email scraper** style lead lists by changing the `googleMapsSearchTerm`. - 🦷 **Dentist and private practice growth**: Use this **dentist email scraper** workflow to find contact emails for individual practices and clinics. - 🧾 **Data enrichment for CRMs**: Feed scraped contact fields into your pipeline for faster onboarding and **doctor email list scraper** operations. - 💻 **Email harvesting tool for doctors**: Generate bulk-ready results for sequencing and list building using dataset exports. - 🔬 **Research and auditing**: Combine business listing metadata with scraped contact fields to assess contact consistency for a **medical email scraper** use case. *** ### Technical specifications - **Supported Input Formats** - ✅ `googleMapsSearchTerm` (string) - ✅ `googleMapsLocation` (array of strings) - ✅ `proxyConfiguration` (object) with `proxy support` - **Proxy Support** - ✅ `proxyConfiguration` with `proxy support` supported - **Dataset Structure** - ✅ Apify dataset named **Business Contact Data** - ✅ Flattened email rows when pushing `email_found` for each email found - **Limit Controls** - ✅ `maxBusinesses` stops collection when reached - ✅ `scrapeMaxBusinessesPerLocation` controls whether limits are per-location or global total - **Limitations** - ❌ Businesses without a website can’t yield scraped emails, and the actor records `scrape_status` as `no_website` in those cases. *** ### FAQ #### Do I need to write code to use Doctors Email Scraper? ✅ No. You can run it directly in Apify Console by filling out the `googleMapsSearchTerm` and `googleMapsLocation` fields and then reviewing results in the dataset. #### What contacts does Doctors Email Scraper extract? ✅ It extracts business listing details (like `name`, `website`, `phone`, address and geo fields) and then scrapes websites for `scraped_emails`, `scraped_phones`, and `scraped_social_media`. It also tracks counts such as `emails_found` and `pages_scraped`. #### How does the actor handle multiple locations? ✅ You can set `scrapeMaxBusinessesPerLocation`. If enabled, it collects up to `maxBusinesses` results per location. If disabled, it combines results across all locations up to a single overall limit. #### Can I limit how many businesses are collected? ✅ Yes. Use `maxBusinesses` (range 1–1000). The scraper stops when the target is reached. #### Where do the results go? ✅ The actor saves results to the Apify dataset **Business Contact Data**, using the dataset fields described in the Output section. Rows are pushed as scraping progresses. #### Is proxy configuration supported? ✅ Yes. You can pass `proxyConfiguration` and set `proxy support` to `true` (pre-filled). Proxies are recommended for large-scale scraping. #### Can you remove data if I don’t need it anymore? ✅ If you need help with data removal or follow-up, contact . *** ### Support & feature requests If you’re using **Doctors Email Scraper** for your doctors email scraper or targeted doctor email outreach tool workflow, we’d love your feedback. 🙌 - 💡 **Feature Requests**: Ideas like CSV-friendly exports, additional normalization, or broader contact field coverage are welcome. - 📧 **Contact**: Send support requests to . Your feedback helps shape improvements to future versions of **Doctors Email Scraper**. *** ### Doctors Email Scraper: final thoughts *If you need a reliable doctors email scraper that turns doctor and clinic listings into structured contact data, **Doctors Email Scraper** is built for scale and speed.*\ *Try it with your `googleMapsSearchTerm` and `googleMapsLocation` and start building your list in minutes.* 🚀 *** ### Disclaimer **This tool accesses publicly accessible sources** to extract business and contact information. It does not access private profiles, authenticated data, or password-protected content. You are responsible for compliance with applicable laws (for example GDPR/CCPA), spam regulations, and each website’s terms of service. For data removal requests, contact . Always use this tool responsibly, ethically, and for legitimate purposes. # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "Doctors", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": 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 = { "googleMapsSearchTerm": "Doctors", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/doctors-email-scraper").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 = { "googleMapsSearchTerm": "Doctors", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("scraperoka/doctors-email-scraper").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 '{ "googleMapsSearchTerm": "Doctors", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call scraperoka/doctors-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/doctors-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Doctors Email Scraper", "description": "🩺 Doctors Email Scraper extracts verified doctors’ emails from targeted directories and profiles. Save time on outreach with GDPR-aware workflows. 🚀 Perfect for B2B lead generation, marketing, and recruitment—find the right contacts fast.", "version": "1.0", "x-build-id": "mRhNoO6WlWGPX3Upe" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~doctors-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-doctors-email-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~doctors-email-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-doctors-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~doctors-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-doctors-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "googleMapsLocation", "googleMapsSearchTerm" ], "properties": { "googleMapsSearchTerm": { "title": "Search Term", "type": "string", "description": "Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists').", "default": "Doctors" }, "googleMapsLocation": { "title": "Location", "type": "array", "description": "Target geographic location for the email scraper (e.g., 'Miami, Florida').", "default": [ "New York" ], "items": { "type": "string" } }, "maxBusinesses": { "title": "Maximum Businesses With Emails", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 5 }, "scrapeMaxBusinessesPerLocation": { "title": "Scrape Max Businesses Per Location", "type": "boolean", "description": "If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```