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jlucasmcrell

Apify Public Data & Leads

mcp-name: io.github.jlucasmcrell/apify-scrapers

Apify Public Data Scrapers & Extractors

Python 3.10+ Node.js 18+ Apify Verified License: MIT

A curated collection of reliable, production-ready scrapers and public-data extractors hosted on the Apify Store.

Each actor is built with strict schema validation, deterministic field mapping, self-healing DOM selectors, and pay-per-event pricing starting at $0.0002 / start.


Quick Navigation


Available Extractors & Store Listings

Tool

Store Link

Key Output Fields

Best For

Google Maps Business Leads

captainhandsome/google-maps-business-search

Name, phone, website, rating, reviews, address, coordinates, hours

B2B lead generation, local agency prospecting

Glassdoor Jobs & Salaries

captainhandsome/glassdoor-jobs-scraper

Title, company, salary estimate, rating, location, job URL, posting date

Hiring intelligence, compensation benchmarking

Airbnb Vacation Rentals

captainhandsome/airbnb-listings-search

Title, room type, nightly price, rating, reviews count, listing URL

Real estate research, market rate tracking

SEC EDGAR Corporate Filings

captainhandsome/sec-edgar-filings-search

Ticker, CIK, form (10-K, 10-Q, 8-K), filing date, primary document URL

Financial diligence, equity research, compliance

USAspending Federal Awards

captainhandsome/usaspending-federal-awards

Recipient vendor, award amount, awarding agency, description, dates

Government contracting, procurement intel

LinkedIn Public Jobs

captainhandsome/linkedin-public-jobs-search

Job title, employer, location, direct apply URL, posting age

Recruitment, tech talent monitoring

Google Play App Reviews

captainhandsome/google-play-reviews-scraper

Review text, star score, thumbs up, date, reviewer name

App store sentiment, competitor feedback

YouTube Video Search

captainhandsome/youtube-search-scraper

Title, video URL, channel, views count, duration, publish date

Content tracking, creator outreach

Twitch Live Streams

captainhandsome/twitch-live-streams-scraper

Streamer username, title, viewer count, language, category

Esports analytics, live stream monitoring

US Contractor Licenses

captainhandsome/us-contractor-license-search

Contractor name, license number, classification, status, state

Trades verification, subcontractor diligence

US Business Entity Registries

captainhandsome/us-business-entity-search

Legal entity name, filing number, jurisdiction, status

Legal due diligence, corporate registration checks


Python Quickstart

1. Install dependencies

pip install apify-client pandas python-dotenv

2. Export 50 Google Maps Leads to CSV

import os
from apify_client import ApifyClient
import pandas as pd

# Get your API token from https://console.apify.com/account/integrations
client = ApifyClient(os.getenv("APIFY_TOKEN"))

# Run the actor
run = client.actor("captainhandsome/google-maps-business-search").call(run_input={
    "search_query": "commercial electricians",
    "location": "Dallas, Texas",
    "max_items": 50,
    "include_details": True,
})

# Fetch dataset items and export to CSV
items = list(client.dataset(run["defaultDatasetId"]).iterate_items())
df = pd.DataFrame(items)
df.to_csv("dallas_electricians.csv", index=False)
print(f"Exported {len(df)} leads to dallas_electricians.csv")

See examples/google_maps_leads_to_csv.py for the full script.


Node.js Quickstart

1. Install dependencies

npm install apify-client

2. Query SEC EDGAR Filings

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

const run = await client.actor('captainhandsome/sec-edgar-filings-search').call({
  companies: ['AAPL', 'NVDA', 'MSFT'],
  forms: ['10-K'],
  max_items: 15,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(filing => {
  console.log(`[${filing.ticker}] ${filing.form} (${filing.filing_date}): ${filing.primary_document_url}`);
});

See examples/sec_filings.js for the full script.


No-Code & Automation Workflows

If you automate via n8n, Make, Zapier, or Google Sheets, ready-to-import blueprints are included in workflows/:


Pre-Built Example Tasks (Zero Code)

If you prefer runnable web UI tasks without writing any code, each actor includes pre-configured tasks published on Apify Store:

Google Maps Leads

Glassdoor Jobs

Airbnb Rentals

YouTube & Google Play


Free Sample Datasets

Looking for clean data to benchmark, analyze, or train models? Verified sample bundles with metadata schemas are available in datasets/ and hosted publicly on Hugging Face Datasets:

  1. Phoenix HVAC Contractor Leads: datasets/phoenix_hvac_leads/ | Hugging Face Hub (20 verified HVAC contractor profiles with ratings, addresses, and phone numbers).

  2. California Licensed Contractors: datasets/california_solar_contractors/ | Hugging Face Hub (Active C-46 and B licensed solar installers with state verification numbers).

  3. Austin Software Engineer Postings: datasets/austin_software_jobs/ | Hugging Face Hub (Normalized job listings with estimated posting dates and salary ranges).


AI Agent & MCP Integration

All actors in this repository conform to OpenAPI and JSON Schema standards, making them directly callable by AI agents via the Model Context Protocol (MCP):

Option A: Hosted Apify MCP Server (Claude Desktop / Cursor)

Add this to your claude_desktop_config.json or Cursor MCP settings:

{
  \"mcpServers\": {
    \"apify\": {
      \"command\": \"npx\",
      \"args\": [\"-y\", \"@apify/mcp-server\"],
      \"env\": {
        \"APIFY_TOKEN\": \"YOUR_APIFY_API_TOKEN\"
      }
    }
  }
}

Option B: Local Lightweight Python MCP Server

For local agent workflows without Node.js dependencies, a direct Python MCP server is included:

export APIFY_TOKEN=\"your_token_here\"
python mcp_server.py

Inspect tools and capabilities via mcp.json.

Agent Prompts That Work Out-of-the-Box:

  • "Search Google Maps for 50 commercial roofers in Atlanta with phone numbers and websites."

  • "Retrieve Apple and Microsoft Form 10-K filings from SEC EDGAR for the last 2 years."

  • "Find the 30 newest reviews for Duolingo on Google Play and analyze negative feedback."


In-Depth Engineering Guides

Technical case studies and problem-solution writeups are located in articles/:


Repository Structure

apify-scrapers/
 README.md                                # Documentation and quickstart
 LICENSE                                  # MIT License
 requirements.txt                         # Python client dependencies
 package.json                             # Node.js dependencies
 mcp.json                                 # MCP tool registry specification
 mcp_server.py                            # Native Python stdio MCP server
 articles/                                # In-depth engineering case studies
    airbnb_playwright_pagination_guide.md
    glassdoor_posting_dates_guide.md
    reddit_community_responses.md        # Reference technical answers for forums
 datasets/                                # Sample benchmark datasets
    phoenix_hvac_leads/
    california_solar_contractors/
    austin_software_jobs/
 workflows/                               # No-code automation templates
    n8n_google_maps_to_sheets.json
    n8n_sec_edgar_to_slack.json
    README.md
 examples/                                # Standalone developer scripts
     google_maps_leads_to_csv.py
     sec_edgar_filings_downloader.py
     glassdoor_jobs_tracker.py
     airbnb_market_scraper.py
     usaspending_defense_awards.py
     twitch_live_stream_monitor.py
     google_maps_leads.js
     sec_filings.js

Author & Support

Maintained by Joseph McRell.


License

This project is licensed under the MIT License - see the LICENSE file for details.