# Attorney Email Scraper (`solid-scraper/attorney-email-scraper`) Actor ⚖️ Attorney Email Scraper extracts verified law-firm contacts fast using targeted keywords, practice areas, and locations—ideal for legal marketing, BD, and outreach teams. 📩🔎 Start finding qualified prospects instantly. - **URL**: https://apify.com/solid-scraper/attorney-email-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 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 ### Attorney Email Scraper 📬 **Attorney Email Scraper** helps you find attorneys and extract their contact information from publicly available sources—so you can build an attorney contact database without spending days manually searching. It’s a **legal email scraper** designed for use cases like targeted attorney email scraping and finding attorney email addresses at scale. Whether you’re a marketer, researcher, or data analyst, this tool makes it easier to compile an attorney outreach email list by combining business discovery with website contact extraction, saving you hours of manual work. --- ### Why choose Attorney Email Scraper? | Feature | Benefit | |---|---| | ✅ All-in-one workflow (business discovery → website contact extraction) | Extracts emails, phone numbers, and social media profiles in one run | | ✅ Reliability-focused scraping with retries and fallbacks | Helps keep results flowing even when some pages are hard to access | | ✅ Structured, dataset-ready output | Saves consistent fields like `name`, `website`, `scraped_emails`, and `scrape_status` for easy analysis | | ✅ Scale-friendly targeting with limits | Stops when you reach your requested number of businesses with emails | | ✅ Built-in proxy support for reliable scraping | Improves robustness for larger batches and helps reduce scraping interruptions | | ✅ Real-time dataset saving | Pushes results to the Apify dataset immediately while it runs | --- ### Key features - 🔍 **Attorney-focused business discovery**: Uses your `googleMapsSearchTerm` and `googleMapsLocation` inputs to target relevant businesses. - 📧 **Email harvesting from websites**: Extracts email addresses and supports email harvesting tool for lawyers workflows. - 📞 **Phone and social media extraction**: Pulls `scraped_phones` and `scraped_social_media` alongside scraped emails. - 🧠 **Smart limits for results**: Lets you control `maxBusinesses` and (optionally) apply the limit per location for controlled attorney prospecting email tool runs. - 🛡️ **Proxy resilience**: Supports `proxyConfiguration` so you can run more reliably at larger scale. - 🔄 **Resilience for difficult sites**: Includes retries and fallbacks to improve completion rates across different domains. - 💾 **Immediate dataset saving**: Pushes each scraped business (and per-email rows when emails are found) into the output dataset as it goes. - 📊 **Dataset fields built for analysis**: Includes location and scoring-style fields like `avg_rating`, `total_reviews`, `lat`, `long`, and `place_id`. --- ### Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Attorney", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `googleMapsSearchTerm` | Yes | Business type or niche for the email scraper (for example, “Attorney”). | | `googleMapsLocation` | Yes | Target geographic location(s) as a list (for example, “New York”). | | `maxBusinesses` | No | Maximum number of businesses to find (range: 1–1000). The actor stops when it reaches the target number. | | `scrapeMaxBusinessesPerLocation` | No | If enabled, it collects up to `maxBusinesses` results **per location**; if disabled, it combines locations up to a single total limit. | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for larger-scale runs. You can enable Apify proxy with `proxy support`. | | `proxyConfiguration.proxy support` | No | When set to `true`, the actor uses Apify proxy (configured as prefilled by default). | *** ### Output The actor saves results into an Apify dataset (JSON rows). Each dataset row includes the business details plus extracted contact information. #### Example output JSON (dataset rows) ```json { "name": "Example Law Firm", "website": "https://examplelawfirm.com", "phone": "+1-555-123-4567", "full_address": "123 Main St Exampletown NY 10001 US", "city": "Exampletown", "state": "NY", "zip": "10001", "country_code": "US", "scraped_emails": ["info@examplelawfirm.com"], "scraped_phones": ["+1-555-111-2222"], "scraped_social_media": ["https://www.linkedin.com/company/examplelawfirm/"], "emails_found": 1, "pages_scraped": 5, "avg_rating": 4.6, "total_reviews": 128, "lat": 40.7128, "long": -74.006, "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "scrape_status": "success" } ``` > Note: When emails are found, the actor flattens output so you may see one row per email with an `email_found` field instead of `scraped_emails`. #### Output Fields | Field | Type | Description | |---|---|---| | `name` | string | Business name. | | `website` | string | Business website URL (if available). | | `phone` | string | Phone number from the business record (if available). | | `full_address` | string | Full address string. | | `city` | string | City portion of the address. | | `state` | string | State/region portion of the address. | | `zip` | string | ZIP/postal code. | | `country_code` | string | Country code. | | `scraped_emails` | array | Emails extracted from the business website (empty array if none). | | `scraped_phones` | array | Phone numbers extracted from the business website. | | `scraped_social_media` | array | Social media profile links extracted from the business website. | | `emails_found` | number | Count of emails found on the scraped website. | | `pages_scraped` | number | Number of processed pages/URLs during website scraping. | | `avg_rating` | number | Average rating value from the business listing data. | | `total_reviews` | number | Total review count from the business listing data. | | `lat` | number | Latitude value for the business location. | | `long` | number | Longitude value for the business location. | | `place_id` | string | Place identifier from the business listing data. | | `scrape_status` | string | Status of the scraping workflow for that row (e.g., `success`, `failed`, `no_website`, `error`). | | `email_found` | string | The specific email for that flattened row (present when the actor outputs per-email rows). | | `scrape_error` | string | Error details when the scrape fails (`scrape_status` indicates failure). | You can export dataset results from Apify as JSON and CSV. *** ### How to use Attorney 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**\ Search for **Attorney Email Scraper** in the Actors marketplace. 3. **Open the Input panel**\ Click the **Input** section and fill in: - `googleMapsSearchTerm` - `googleMapsLocation` (use a list) 4. **Set your result limits**\ Adjust `maxBusinesses` to control how many businesses you want. If you’re running multiple locations, choose whether to enable `scrapeMaxBusinessesPerLocation`. 5. **(Optional) Configure proxies**\ In `proxyConfiguration`, enable `proxy support` if you want the actor to use Apify proxy support for more reliable scraping. 6. **Click Run**\ Start the actor. You’ll see progress in the logs and dataset rows will be pushed as contact information is extracted. 7. **Review the dataset output**\ After the run, open the **OUTPUT** tab to view the dataset: - Each row includes business fields plus extracted contact fields like `scraped_emails`, `scraped_phones`, and `scraped_social_media`. 8. **Export your results**\ Export to JSON or CSV for your attorney contact database, legal email scraper pipeline, or downstream analysis. No coding required—get accurate attorney email scraper results in minutes. *** ### Advanced features & SEO optimization - 🏛️ **Built for attorney email outreach lists**: Designed specifically for finding attorney email addresses and building a legal industry email database from business and website sources. - 🌐 **Public-web contact extraction**: Extracts emails and additional contact details from websites for each discovered business, supporting attorney lead email list creation. - 🛡️ **Proxy resilience for scraping at scale**: Uses your `proxyConfiguration` to improve reliability and reduce interruptions during larger scraping tasks. - 🧾 **Flattened dataset rows when emails are found**: Supports both “scraped lists” and per-email rows (including `email_found`) so CRM import workflows can be easier. - 📊 **Rich structured location fields**: Output includes `full_address`, `city`, `state`, `zip`, `lat`, `long`, and `place_id`—useful for segmentation and analysis. *** ### Best use cases - 📈 **Lead generation for law firms**: Build an attorney outreach email list with emails scraped from websites. - 🧪 **Market research and competitive analysis**: Compare law firms by location using `avg_rating`, `total_reviews`, `city`, and `state` alongside contacts. - 🎯 **Sales prospecting**: Generate targeted attorney email scraping results for B2B outreach with an attorney contact database. - 🗂️ **Research teams & analysts**: Export structured rows (including `lat`, `long`, `place_id`) for geospatial or segmentation analysis. - 🧑‍💻 **Data pipeline builders**: Use the dataset fields to enrich lists with `scraped_phones` and `scraped_social_media` for higher-touch outreach. - ✉️ **Email marketing ops**: Combine contact emails with business metadata to automate campaign list creation (starting from publicly available data). *** ### Technical specifications - **Supported Input Formats** - ✅ `googleMapsSearchTerm` (string) - ✅ `googleMapsLocation` (array of strings) - ✅ `maxBusinesses` (integer 1–1000) - ✅ `scrapeMaxBusinessesPerLocation` (boolean) - ✅ `proxyConfiguration` (object, including `proxy support`) - **Proxy Support** - ✅ `proxyConfiguration` supported via the Apify proxy option (`proxy support` prefilled to `true`). - **Retry Mechanism** - ✅ Includes retries and fallbacks for resilient scraping behavior (to improve success across different domains). - **Dataset Structure** - ✅ Business-level fields + scraped contact fields - ✅ Includes `scraped_emails`, `scraped_phones`, `scraped_social_media`, plus counts like `emails_found` and `pages_scraped` - ✅ Includes status via `scrape_status` and failure details via `scrape_error` when applicable - ✅ May include per-email flattened rows via `email_found` - **Rate Limits & Performance** - ✅ Controlled by batching limits (`maxBusinesses`, and optionally per-location behavior) - **Limitations** - ❌ If a business has no website, the actor will mark `scrape_status` as `no_website` and there will be no scraped contacts from a website. - ❌ Some websites may not expose contact information publicly, resulting in `scrape_status` of `failed` or empty `scraped_emails`. *** ### FAQ #### Does Attorney Email Scraper only work for attorneys? ✅ Yes—this actor is intended for attorney-focused business discovery using the `googleMapsSearchTerm` you provide (prefilled to “Attorney”) and targeted location(s) via `googleMapsLocation`. #### What contact details does Attorney Email Scraper extract? ✅ It extracts email addresses into `scraped_emails`, plus phone numbers and social media profile links into `scraped_phones` and `scraped_social_media`. It also outputs counts like `emails_found` and `pages_scraped`. #### Do I get results per business or per email? ✅ Both patterns can appear in the dataset. When emails are found, the actor flattens output so you may see one row per email using `email_found`. Business-level fields still include the context (like `name`, `website`, `place_id`, and `scrape_status`). #### Can I control how many businesses are scraped? ✅ Yes. Use `maxBusinesses` to set the overall target. If you enable `scrapeMaxBusinessesPerLocation`, the actor targets up to `maxBusinesses` per location instead of a single combined total. #### Is proxy support available for Attorney Email Scraper? ✅ Yes. You can configure `proxyConfiguration` and enable `proxy support` for more reliable scraping at scale. #### Can the actor validate emails before saving? ✅ You can control email validation via the input (internally referenced as `validateEmails`). If enabled, it supports validation behavior; dataset rows still include `scraped_emails` and `emails_found`. #### Is the data sourced from publicly available sources? ✅ Yes. The actor collects information from **publicly available sources**. It does not access private, authenticated, or password-protected content. *** ### Support & feature requests If you’re using Attorney Email Scraper and want improvements (for example, exporting formats or CRM-friendly tweaks), we’d love your feedback. - 💡 **Feature Requests**: Share concrete enhancements like CSV-ready fields, additional normalization options, or different flattening behavior for `email_found`. - 📧 **Contact**: Send a message to . User feedback directly shapes what we build next for Attorney Email Scraper. *** ### Disclaimer **This tool only accesses publicly available sources.** It does not access private profiles, authenticated data, or password-protected pages. It’s your responsibility to comply with applicable laws (including GDPR/CCPA where relevant), spam regulations, and each website’s terms of service. For data removal requests, contact . Use Attorney Email Scraper responsibly, ethically, and for legitimate purposes only. *Get the most comprehensive Attorney Email Scraper results—SEO-optimized, dataset-ready, and built for scaling attorney lead generation.* # 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": "Attorney", "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": "Attorney", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/attorney-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": "Attorney", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/attorney-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": "Attorney", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call solid-scraper/attorney-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/attorney-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Attorney Email Scraper", "description": "⚖️ Attorney Email Scraper extracts verified law-firm contacts fast using targeted keywords, practice areas, and locations—ideal for legal marketing, BD, and outreach teams. 📩🔎 Start finding qualified prospects instantly.", "version": "1.0", "x-build-id": "NxhJkB0s0a555Az0Q" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~attorney-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-attorney-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~attorney-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-attorney-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~attorney-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-attorney-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Attorney" }, "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 } } } } } } } } } } ```