# Mass LinkedIn Scraper w/ Email (`ayeeyee/mass-linkedin-scraper-w-email`) Actor Mass LinkedIn Scraper w/ Email returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing. - **URL**: https://apify.com/ayeeyee/mass-linkedin-scraper-w-email.md - **Developed by:** [Virtual Footprint LLC](https://apify.com/ayeeyee) (community) - **Categories:** Lead generation, Open source - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Mass LinkedIn Scraper w/ Email Extract LinkedIn and B2B prospecting data with Mass LinkedIn Scraper w/ Email in a structured, automation-ready format. ### Features - Collect profile, company, and role-level attributes - Extract contact-enrichment friendly records for CRM workflows - Support prospecting queries and direct profile/company URLs - Return normalized fields for lead scoring and enrichment - Batch-friendly for outbound and GTM pipelines - Supports keyword and query-based discovery inputs - Output is optimized for Mass LinkedIn Scraper w/ Email buyer workflows on Apify ### Common Use Cases - Lead generation - Account research - Sales prospecting - CRM enrichment - Recruiting intelligence - Competitive benchmarking ### Example Input ```json { "query": "site:linkedin.com/in machine learning engineer", "queries": [ "market research" ], "urls": [ "https://www.linkedin.com/company/microsoft/" ], "maxResults": 25, "includeRaw": false, "maxCostPerRun": 5 } ```` ### Example Output ```json { "query": "site:linkedin.com/in machine learning engineer", "url": "https://www.linkedin.com/company/microsoft/", "actorSlug": "record value", "source": "record value", "title": "record value", "description": "record value", "scrapedAt": "record value" } ``` ### Input Parameters | Field | Type | Required | Description | | --- | --- | --- | --- | | query | string | No | Primary keyword, URL, profile, company, product, or identifier to collect | | queries | array | No | Optional batch list of query strings. Used when query is empty or when batching is… | | urls | array | No | Optional direct URLs to process. These take priority over discovery when provided | | maxResults | integer | No | Maximum number of dataset items to emit | | includeRaw | boolean | No | Include collection diagnostics and raw source metadata where available | | maxCostPerRun | number | No | Optional guardrail in USD. The actor caps output before exceeding this amount | | proxyConfiguration | object | No | Apify proxy settings for production runs | ### Output Fields | Field | Type | Description | | --- | --- | --- | | query | string | Normalized query value | | url | string | Normalized url value | | actorSlug | string | Normalized actorSlug value | | source | string | Normalized source value | | title | string | Normalized title value | | description | string | Normalized description value | | scrapedAt | string | Normalized scrapedAt value | | runId | string | Normalized runId value | | rank | string | Normalized rank value | | name | string | Normalized name value | | company | string | Normalized company value | | role | string | Normalized role value | ### Export Formats - JSON - CSV - Excel - XML ### Pricing Pricing Model: PAY\_PER\_EVENT $3.00 per 1,000 dataset items. ### FAQ #### Does this actor support batch processing? Yes. #### Can I export results to CSV? Yes. #### Can I schedule runs? Yes, through Apify schedules. #### Can I run this actor via API? Yes, via the Apify API. #### Does it support direct URLs? Yes. #### Can I integrate this actor with n8n or Make? Yes. # Actor input Schema ## `query` (type: `string`): Primary keyword, URL, profile, company, product, or identifier to collect. ## `queries` (type: `array`): Optional batch list of query strings. Used when query is empty or when batching is desired. ## `urls` (type: `array`): Optional direct URLs to process. These take priority over discovery when provided. ## `maxResults` (type: `integer`): Maximum number of dataset items to emit. ## `maxCostPerRun` (type: `number`): Optional guardrail in USD. The actor caps output before exceeding this amount. ## `includeRaw` (type: `boolean`): Include collection diagnostics and raw source metadata where available. ## `proxyConfiguration` (type: `object`): Apify proxy settings for production runs. ## Actor input object example ```json { "maxResults": 25, "maxCostPerRun": 5, "includeRaw": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ayeeyee/mass-linkedin-scraper-w-email").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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("ayeeyee/mass-linkedin-scraper-w-email").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call ayeeyee/mass-linkedin-scraper-w-email --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ayeeyee/mass-linkedin-scraper-w-email", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Mass LinkedIn Scraper w/ Email", "description": "Mass LinkedIn Scraper w/ Email returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing.", "version": "1.0", "x-build-id": "9JW0azxRzOwX1qzCz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ayeeyee~mass-linkedin-scraper-w-email/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ayeeyee-mass-linkedin-scraper-w-email", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ayeeyee~mass-linkedin-scraper-w-email/runs": { "post": { "operationId": "runs-sync-ayeeyee-mass-linkedin-scraper-w-email", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ayeeyee~mass-linkedin-scraper-w-email/run-sync": { "post": { "operationId": "run-sync-ayeeyee-mass-linkedin-scraper-w-email", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "query": { "title": "Query", "type": "string", "description": "Primary keyword, URL, profile, company, product, or identifier to collect." }, "queries": { "title": "Queries", "type": "array", "description": "Optional batch list of query strings. Used when query is empty or when batching is desired.", "items": { "type": "string" } }, "urls": { "title": "Direct URLs", "type": "array", "description": "Optional direct URLs to process. These take priority over discovery when provided.", "items": { "type": "string" } }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of dataset items to emit.", "default": 25 }, "maxCostPerRun": { "title": "Maximum cost per run", "minimum": 0.01, "type": "number", "description": "Optional guardrail in USD. The actor caps output before exceeding this amount.", "default": 5 }, "includeRaw": { "title": "Include raw metadata", "type": "boolean", "description": "Include collection diagnostics and raw source metadata where available.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify proxy settings for production runs.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```