# My Actor 6 (`red.cars/b2b-lead-gen-suite-mcp`) Actor - **URL**: https://apify.com/red.cars/b2b-lead-gen-suite-mcp.md - **Developed by:** [AutomateLab](https://apify.com/red.cars) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% 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 ## B2B Lead Gen Suite MCP [![Apify Actor](https://img.shields.io/badge/Apify-Actor-blue?logo=apify)](https://apify.com) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Node](https://img.shields.io/badge/Node-22+-green.svg)](https://nodejs.org/) > Comprehensive B2B lead generation suite for scraping company info, contacts, and generating qualified leads from LinkedIn, company websites, and business directories. ### 🎯 Overview B2B Lead Gen Suite MCP is an AI-agent-optimized actor that provides enterprise-grade lead generation capabilities with Pay-Per-Event (PPE) pricing. It implements `handleRunFunction` with four core operations: `scrapeCompanies`, `scrapeContacts`, `generateLeads`, and `exportCSV`. #### Key Features - **Multi-Source Scraping**: LinkedIn, company websites, business directories - **PPE (Pay-Per-Event) Pricing**: Only pay for successful extractions - **handleRunFunction API**: Simple operation dispatcher for AI agents - **ERROR_RETRY Handling**: Exponential backoff with 3 retry attempts - **Agent Handshake**: <5 second smoke test with FREE compute - **CSV/JSON Export**: Flexible export formats for CRM integration ### ⚡ Quick Start #### 1. Installation ```bash ## Navigate to project directory cd ~/Projects/apify-actors/b2b-lead-gen-suite-mcp ## Install dependencies npm install ```` #### 2. Local Development ```bash ## Run locally with Apify SDK apify run ## Or set input via environment APIFY_INPUT_DEFAULT={"operation":"generateLeads","queries":["Software Engineer at Google"],"maxResults":5} npx apify run ``` #### 3. Push to Apify ```bash apify push ``` ### 📋 Input Schema #### Core Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `operation` | string | Operation to perform: `scrapeCompanies`, `scrapeContacts`, `generateLeads`, `exportCSV` | `generateLeads` | | `sources` | array | Sources to scrape: `linkedin`, `company_websites`, `business_directories`, `all` | `["linkedin"]` | | `queries` | array | Search terms for lead generation | `["Tech companies in San Francisco"]` | | `maxResults` | integer | Maximum results per operation (1-1000) | `10` | | `companyDomains` | array | List of company domains (e.g., `["google.com", "microsoft.com"]`) | `[]` | | `linkedInUrls` | array | LinkedIn profile URLs for contact scraping | `[]` | | `exportFormat` | string | Export format: `csv`, `json`, `xlsx` | `csv` | | `includeHeaders` | boolean | Include column headers in CSV export | `true` | | `proxyType` | string | Proxy type: `DATACENTER`, `RESIDENTIAL` | `DATACENTER` | | `debugMode` | boolean | Enable minimal extraction for testing (300s max) | `false` | | `checkOnly` | boolean | 5-second handshake test (FREE compute) | `false` | #### Example Input ```json { "operation": "generateLeads", "sources": ["linkedin", "company_websites"], "queries": ["Software Engineer at Google", "Product Manager at Microsoft"], "maxResults": 20, "companyDomains": ["google.com", "microsoft.com"], "exportFormat": "csv", "includeHeaders": true, "proxyType": "RESIDENTIAL", "debugMode": false, "checkOnly": false } ``` ### 🔧 handleRunFunction API The `handleRunFunction` provides a simple dispatcher for all operations: #### Operations ##### 1. scrapeCompanies Extract company information from multiple sources. ```javascript { "operation": "scrapeCompanies", "sources": ["linkedin", "company_websites", "business_directories"], "companyDomains": ["google.com", "apple.com"], "maxResults": 50 } ``` **Returns:** Array of company objects with id, name, domain, industry, size, location, linkedinUrl, source, scrapedAt. ##### 2. scrapeContacts Extract contact information from LinkedIn profiles. ```javascript { "operation": "scrapeContacts", "linkedInUrls": [ "https://www.linkedin.com/in/johndoe", "https://www.linkedin.com/in/janesmith" ], "maxResults": 25 } ``` **Returns:** Array of contact objects with id, fullName, jobTitle, company, email, phone, linkedinUrl, location, source, scrapedAt. ##### 3. generateLeads Generate qualified B2B leads from multiple sources. ```javascript { "operation": "generateLeads", "sources": ["linkedin", "company_websites"], "queries": ["Software Engineer at Google", "Data Scientist at Meta"], "maxResults": 100, "companyDomains": ["google.com", "meta.com"] } ``` **Returns:** Array of lead objects with id, fullName, jobTitle, company, email, linkedinUrl, source, quality, generatedAt. ##### 4. exportCSV Export results to CSV or JSON format. ```javascript { "operation": "exportCSV", "results": [], // Uses generateLeads if empty "exportFormat": "csv", "includeHeaders": true, "queries": ["Tech companies"], "maxResults": 50 } ``` **Returns:** Export file with filename, format, recordCount, exportedAt. ### 💰 PPE Pricing This actor uses Pay-Per-Event (PPE) pricing model. You only pay for successful extractions: | Event | FREE Tier | BRONZE | SILVER | GOLD | |-------|-----------|--------|--------|------| | Actor Start | $0.00005 | $0.00005 | $0.00005 | $0.00005 | | Company Scraped | $0.05 | $0.035 | $0.02 | $0.01 | | Contact Scraped | $0.08 | $0.055 | $0.03 | $0.015 | | Lead Generated | $0.10 | $0.075 | $0.04 | $0.02 | | CSV Exported | $0.02 | $0.02 | $0.02 | $0.02 | #### Zero-Result Guard PPE charging only occurs when actual data is extracted. If no results are found, no charges are applied. ### 🔄 ERROR\_RETRY Handling The actor implements robust error handling with exponential backoff: ```javascript async function withRetry(fn, maxRetries = 3, baseDelayMs = 1000) { for (let attempt = 1; attempt <= maxRetries; attempt++) { try { return await fn(); } catch (error) { if (attempt < maxRetries) { const delay = baseDelayMs * Math.pow(2, attempt - 1); await sleep(delay); } } } throw lastError; } ``` #### Retry Conditions - Network timeouts - Rate limiting (429 responses) - Temporary server errors (5xx) - CAPTCHA detection with fallback ### 🤖 AI Agent Integration #### 5-Second Handshake For AI agent smoke tests, use `checkOnly: true`: ```javascript { "checkOnly": true, "maxResults": 10 } ``` Returns readiness status in <5 seconds with FREE compute. #### handleRunFunction Example ```javascript const result = await handleRunFunction({ operation: 'generateLeads', sources: ['linkedin'], queries: ['Software Engineer at Google'], maxResults: 50, proxyType: 'RESIDENTIAL' }); ``` ### 📊 Output Schema All operations return: ```json { "success": true, "operation": "generateLeads", "results": [...], "resultsCount": 50, "exportedFile": "", "charges": [], "scrapedAt": "2026-05-19T21:00:00.000Z", "durationMs": 2500 } ``` #### Result Objects **Company:** ```json { "id": "lead_123456_abc123", "name": "Google", "domain": "google.com", "linkedinUrl": "https://linkedin.com/company/google", "industry": "Technology", "size": "10000+", "location": "Mountain View, CA", "source": "linkedin", "scrapedAt": "2026-05-19T21:00:00.000Z" } ``` **Contact:** ```json { "id": "lead_123456_def456", "fullName": "John Doe", "jobTitle": "Software Engineer", "company": "Google", "email": "john.doe@example.com", "phone": "+1-555-0100", "linkedinUrl": "https://linkedin.com/in/johndoe", "location": "San Francisco, CA", "source": "linkedin", "scrapedAt": "2026-05-19T21:00:00.000Z" } ``` **Lead:** ```json { "id": "lead_123456_ghi789", "fullName": "Jane Smith", "jobTitle": "Product Manager", "company": "Microsoft", "email": "jane.smith@example.com", "linkedinUrl": "https://linkedin.com/in/janesmith", "source": "google_serp_linkedin", "quality": "high", "generatedAt": "2026-05-19T21:00:00.000Z" } ``` ### 🚀 Usage Examples #### Basic Lead Generation ```bash apify run -c '{ "operation": "generateLeads", "queries": ["Software Engineer at Google"], "maxResults": 10 }' ``` #### Scrape Multiple Companies ```javascript { "operation": "scrapeCompanies", "sources": ["linkedin", "company_websites"], "companyDomains": ["google.com", "microsoft.com", "apple.com"], "maxResults": 50, "proxyType": "RESIDENTIAL" } ``` #### Contact Discovery ```javascript { "operation": "scrapeContacts", "linkedInUrls": [ "https://www.linkedin.com/in/johndoe", "https://www.linkedin.com/in/janesmith", "https://www.linkedin.com/in/bobwilson" ], "maxResults": 25 } ``` #### Export to CSV ```javascript { "operation": "exportCSV", "results": [], // Uses generateLeads if empty "exportFormat": "csv", "includeHeaders": true, "queries": ["Tech companies in San Francisco"], "maxResults": 100 } ``` ### 🛠️ Configuration #### Proxy Configuration | Type | Use Case | Cost | |------|----------|------| | `DATACENTER` | General web scraping, faster | Lower | | `RESIDENTIAL` | High-security targets (LinkedIn) | Higher | #### Debug Mode Enable `debugMode: true` for: - Minimal extraction (max 2 results) - Faster proxy (DATACENTER) - 300-second timeout compliance - Health check verification ### 📝 Error Handling | Error | Cause | Solution | |-------|-------|----------| | `EXTRACTION_ERROR` | Profile blocked/private | Use RESIDENTIAL proxy | | `RATE_LIMIT_ERROR` | Too many requests | Reduce concurrency, wait | | `NETWORK_ERROR` | Connectivity issue | Check connection, retry | | `CAPTCHA_BLOCKED` | Google/LinkedIn CAPTCHA | Use RESIDENTIAL proxies | | `AUTH_WALL` | LinkedIn login required | Use Google SERP fallback | ### 🔒 Legal & Compliance **Data Source**: LinkedIn, company websites, business directories **Terms of Service**: This actor is for legitimate data collection only. Users must comply with target platform ToS and applicable laws. **Privacy**: All extracted data is processed per applicable privacy laws. Do not use for unauthorized collection. **Attribution**: Comply with data source attribution requirements. ### 📄 License MIT License - see LICENSE file for details. *** *Built with 🛠️ by seed • [Apify Actor](https://apify.com)* # Actor input Schema ## `operation` (type: `string`): The operation to perform: scrapeCompanies, scrapeContacts, generateLeads, or exportCSV. ## `sources` (type: `array`): Sources to scrape from: linkedin, company\_websites, business\_directories, or all. ## `queries` (type: `array`): Search terms for lead generation (e.g., 'Software Engineer at Google' or company names). ## `maxResults` (type: `integer`): Maximum number of results to extract per operation. ## `companyDomains` (type: `array`): List of company domains to scrape (e.g., \['google.com', 'microsoft.com']). ## `linkedInUrls` (type: `array`): LinkedIn profile URLs for contact scraping. ## `exportFormat` (type: `string`): Format for exported data. ## `includeHeaders` (type: `boolean`): Include column headers in CSV export. ## `proxyType` (type: `string`): Choose your preferred balance of cost vs reliability. Standard (Datacenter) is faster; Premium (Residential) is most reliable for high-security targets. ## `debugMode` (type: `boolean`): Enable minimal extraction for health checks and testing. Guarantees success within 300s. ## `checkOnly` (type: `boolean`): If true, the Actor will verify proxies and estimate cost in < 5 seconds. Use this for AI Agent smoke tests (FREE compute). ## Actor input object example ```json { "operation": "generateLeads", "sources": [ "linkedin" ], "queries": [ "Tech companies in San Francisco" ], "maxResults": 10, "companyDomains": [], "linkedInUrls": [], "exportFormat": "csv", "includeHeaders": true, "proxyType": "DATACENTER", "debugMode": true, "checkOnly": false } ``` # 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 = { "sources": [ "linkedin" ], "queries": [ "Tech companies in San Francisco" ], "maxResults": 10, "includeHeaders": true, "proxyType": "DATACENTER", "debugMode": true }; // Run the Actor and wait for it to finish const run = await client.actor("red.cars/b2b-lead-gen-suite-mcp").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 = { "sources": ["linkedin"], "queries": ["Tech companies in San Francisco"], "maxResults": 10, "includeHeaders": True, "proxyType": "DATACENTER", "debugMode": True, } # Run the Actor and wait for it to finish run = client.actor("red.cars/b2b-lead-gen-suite-mcp").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 '{ "sources": [ "linkedin" ], "queries": [ "Tech companies in San Francisco" ], "maxResults": 10, "includeHeaders": true, "proxyType": "DATACENTER", "debugMode": true }' | apify call red.cars/b2b-lead-gen-suite-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=red.cars/b2b-lead-gen-suite-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "My Actor 6", "version": "0.0", "x-build-id": "kqANHHC7k7sisEnUA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/red.cars~b2b-lead-gen-suite-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-red.cars-b2b-lead-gen-suite-mcp", "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/red.cars~b2b-lead-gen-suite-mcp/runs": { "post": { "operationId": "runs-sync-red.cars-b2b-lead-gen-suite-mcp", "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/red.cars~b2b-lead-gen-suite-mcp/run-sync": { "post": { "operationId": "run-sync-red.cars-b2b-lead-gen-suite-mcp", "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": [ "operation" ], "properties": { "operation": { "title": "Operation", "enum": [ "scrapeCompanies", "scrapeContacts", "generateLeads", "exportCSV" ], "type": "string", "description": "The operation to perform: scrapeCompanies, scrapeContacts, generateLeads, or exportCSV.", "default": "generateLeads" }, "sources": { "title": "Data Sources", "type": "array", "description": "Sources to scrape from: linkedin, company_websites, business_directories, or all.", "default": [ "linkedin" ], "items": { "type": "string" } }, "queries": { "title": "Search Queries", "type": "array", "description": "Search terms for lead generation (e.g., 'Software Engineer at Google' or company names).", "default": [ "Tech companies in San Francisco" ], "items": { "type": "string" } }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of results to extract per operation.", "default": 10 }, "companyDomains": { "title": "Company Domains", "type": "array", "description": "List of company domains to scrape (e.g., ['google.com', 'microsoft.com']).", "default": [], "items": { "type": "string" } }, "linkedInUrls": { "title": "LinkedIn Profile URLs", "type": "array", "description": "LinkedIn profile URLs for contact scraping.", "default": [], "items": { "type": "string" } }, "exportFormat": { "title": "Export Format", "enum": [ "csv", "json", "xlsx" ], "type": "string", "description": "Format for exported data.", "default": "csv" }, "includeHeaders": { "title": "Include Headers in Export", "type": "boolean", "description": "Include column headers in CSV export.", "default": true }, "proxyType": { "title": "Proxy Reliability Level", "enum": [ "DATACENTER", "RESIDENTIAL" ], "type": "string", "description": "Choose your preferred balance of cost vs reliability. Standard (Datacenter) is faster; Premium (Residential) is most reliable for high-security targets.", "default": "RESIDENTIAL" }, "debugMode": { "title": "Debug Mode (Self-Test)", "type": "boolean", "description": "Enable minimal extraction for health checks and testing. Guarantees success within 300s.", "default": false }, "checkOnly": { "title": "Check Only (5-Second Handshake)", "type": "boolean", "description": "If true, the Actor will verify proxies and estimate cost in < 5 seconds. Use this for AI Agent smoke tests (FREE compute).", "default": false } } }, "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 } } } } } } } } } } ```