All-in one Linkedin Scraper

What does All-in-One LinkedIn Scraper do?

All-in-One LinkedIn Scraper extracts structured data from LinkedIn across 6 scraping modes — profiles, companies, jobs, posts, people search, plus a premium Profile Complete tier that bundles profile + posts + engagement into a single result. No cookies needed. No login required. Zero risk to your LinkedIn account.

Most LinkedIn scrapers require your li_at session cookie, putting your account at risk of permanent ban. This scraper works 100% without authentication — it uses public LinkedIn pages and guest APIs only. Replaces 5+ separate LinkedIn scrapers with one all-in-one actor.

Easiest Way to Start: Paste a URL

Just paste any LinkedIn URL into the "LinkedIn URLs" field and hit Start. The scraper auto-detects the mode:

URL Pattern	Auto-Detected Mode
linkedin.com/in/williamhgates	Profiles
linkedin.com/company/microsoft	Companies
linkedin.com/posts/microsoft_...	Posts

For Jobs and Search modes, enter a keyword in the "Search Query" field instead.

6 Scraping Modes

Mode	Description	Best For
Profiles	Full public profile data: experience, education, about, posts	Lead enrichment, recruiting
Companies	Company pages: industry, size, HQ, website, specialties, followers	Market research, B2B targeting
Jobs	Job search with filters: type, experience, location, salary	Job market analysis, recruiting
Posts	Posts from profiles and company pages with engagement data	Content analysis, social listening
Search	Find LinkedIn profiles by keywords and location (multi-source: Voyager API + DDG + Google + Bing)	Prospecting, lead discovery
Profile Complete	Profile + all posts + engagement data in one result	Full person intelligence

Pricing — Pay Per Result, No Monthly Fee

Standard Modes

Mode	Price / result	Price / 1,000	Fields	Best For
Jobs	$0.001	$1.00	16 fields	Job market research, recruiting pipelines
Posts	$0.0015	$1.50	10 fields	Content monitoring, social listening
Companies	$0.002	$2.00	15 fields	B2B market research, competitor tracking
Search	$0.002	$2.00	9 fields	Lead discovery, prospecting
Profiles	$0.0025	$2.50	14 fields	Lead enrichment, recruiting

Premium Tier

Mode	Price / result	Price / 1,000	What's Included	Best For
Profile Complete	$0.005	$5.00	Profile + up to 10 posts with engagement (likes, comments, shares) + total engagement score	Full person intelligence, influencer analysis

Why Profile Complete? Buying Profile + Posts separately costs $4/1K and requires two runs + manual matching. Profile Complete gives you everything in one result for $5/1K — one run, one output, zero hassle.

Apify Subscription Discounts

Higher Apify subscription plans get automatic discounts on all modes:

Apify Plan	Discount Tier	Discount
Free / Starter	Standard	—
Scale	Bronze	5% off
Business	Silver	10% off
Enterprise	Gold	15% off

Cost examples:

• 100 job listings: $0.10
• 500 LinkedIn profiles: $1.25
• 200 company pages: $0.40
• 100 complete person profiles with posts: $0.50

You only pay for results delivered. Platform compute costs are included.

Why Japi Cricket's LinkedIn Scraper?

• No cookies, no login, no risk — your LinkedIn account stays safe (most competitors require li_at)
• 6 modes in one actor — 5 standard + 1 premium Complete tier, one integration to maintain
• Cheapest on Apify — profiles at $2.50/1K vs $10/1K (Dev Fusion), jobs at $1/1K vs $29.99/mo (Bebity), posts at $1.50/1K vs $5/1K (ApiMaestro)
• HTTP-only architecture — Impit with Chrome TLS fingerprint impersonation (no bloated browser)
• 256 MB memory — runs on minimal resources, keeping your compute costs low
• Residential proxy rotation — automatic retry with IP rotation on blocks
• Human-like behavior — randomized delays with Box-Muller distribution jitter
• MCP-compatible — works with AI agents (Claude, GPT, Cursor) out of the box

MCP Integration for AI Agents

This scraper works with AI agents via the Model Context Protocol (MCP). Connect it to Claude Desktop, Cursor, GPT, or any MCP-compatible client.

Setup:

1. Go to mcp.apify.com
2. Add "All-in-One LinkedIn Scraper" to your MCP server
3. Ask your AI: "Find 20 software engineers in San Francisco on LinkedIn"

Example prompts for your AI agent:

• "Scrape the LinkedIn profile of Bill Gates"
• "Search LinkedIn for product managers in New York"
• "Get the latest job postings for data scientist in London"
• "Get the complete profile with posts for Satya Nadella"

Works with Claude Desktop, Cursor, GPT via MCP, and any other MCP-compatible AI client.

Integrations

n8n

1. Add the Apify node in your n8n workflow
2. Select "All-in-One LinkedIn Scraper" as the actor
3. Configure the mode and input parameters
4. Connect the output to your CRM, Google Sheets, or database

Make.com (Integromat)

1. Add the Apify module to your scenario
2. Select "Run Actor" and choose this scraper
3. Map the JSON output fields to your downstream modules
4. Use for automated lead enrichment, job monitoring, or CRM syncing

Zapier

1. Create a new Zap with Apify as the trigger or action
2. Select "Run Actor" and configure with this scraper's actor ID
3. Map output fields to Google Sheets, HubSpot, Salesforce, or Slack
4. Trigger on schedule or from a webhook

REST API & SDKs

Use the Apify API, JavaScript SDK, or Python SDK for programmatic access. See the Python example below.

---

Mode 1: Profiles

Scrape public LinkedIn profile data including experience, education, skills, connections, and recent posts.

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"profiles"
urls	string[]	Yes	LinkedIn profile URLs	linkedin.com/in/username format
maxResults	integer	No	Maximum profiles to return	1–1000, default: 25
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "profiles",
  "urls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/satlokomern"
  ],
  "maxResults": 25
}

Output Fields

Field	Type	Description	Example
mode	string	Always "profiles"	"profiles"
name	string	Full name	"Bill Gates"
headline	string	Profile headline	"Co-chair, Bill & Melinda Gates Foundation"
location	string	Location from profile	"Seattle, Washington, United States"
image_url	string	Profile photo URL	"https://media.licdn.com/..."
url	string	LinkedIn profile URL	"https://www.linkedin.com/in/williamhgates"
current_title	string	Current job title	"Co-chair"
current_company	string	Current employer	"Bill & Melinda Gates Foundation"
connections	integer	Number of connections	500
followers	integer	Number of followers	35800000
about	string	About section text	"Technologist, business leader..."
experience	array	Work history	[{title, company, date_range, duration, location}]
education	array	Education history	[{school, degree, dates}]
recent_posts	array	Last 3 posts	[{title, url, date, likes}]
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "profiles",
  "name": "Bill Gates",
  "headline": "Co-chair, Bill & Melinda Gates Foundation",
  "location": "Seattle, Washington, United States",
  "image_url": "https://media.licdn.com/dms/image/...",
  "url": "https://www.linkedin.com/in/williamhgates",
  "current_title": "Co-chair",
  "current_company": "Bill & Melinda Gates Foundation",
  "connections": 500,
  "followers": 35800000,
  "about": "Technologist, business leader, and philanthropist.",
  "experience": [
    {
      "title": "Co-chair",
      "company": "Bill & Melinda Gates Foundation",
      "date_range": "Jan 2000 - Present",
      "duration": "26 years",
      "location": "Seattle, WA"
    }
  ],
  "education": [
    {
      "school": "Harvard University",
      "degree": "Undergraduate",
      "dates": "1973 - 1975"
    }
  ],
  "recent_posts": [
    {
      "title": "AI and the future of education",
      "url": "https://www.linkedin.com/posts/williamhgates_...",
      "date": "2026-02-20",
      "likes": 45000
    }
  ],
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Lead enrichment: Enrich CRM contacts with LinkedIn profile data (headline, company, location)
• Recruiting: Screen candidates by experience, education, and current role
• Sales prospecting: Identify decision-makers and their current titles
• Competitor intelligence: Track key people at competitor companies

How to Run

Apify Console:

1. Go to All-in-One LinkedIn Scraper on Apify
2. Select Profiles mode
3. Paste LinkedIn profile URLs
4. Click Start

Python:

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "profiles",
    "urls": [
        "https://www.linkedin.com/in/williamhgates",
        "https://www.linkedin.com/in/satyanadella"
    ],
    "maxResults": 25
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} — {item['headline']} — {item['location']}")

---

Mode 2: Companies

Scrape public LinkedIn company pages including industry, size, headquarters, website, specialties, and recent posts.

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"companies"
urls	string[]	Yes	LinkedIn company URLs	linkedin.com/company/name format
maxResults	integer	No	Maximum companies to return	1–1000, default: 25
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "companies",
  "urls": [
    "https://www.linkedin.com/company/microsoft",
    "https://www.linkedin.com/company/google"
  ],
  "maxResults": 25
}

Output Fields

Field	Type	Description	Example
mode	string	Always "companies"	"companies"
name	string	Company name	"Microsoft"
description	string	Company description	"Every company has a mission..."
url	string	LinkedIn company URL	"https://www.linkedin.com/company/microsoft"
website	string	Company website	"https://www.microsoft.com"
logo	string	Company logo URL	"https://media.licdn.com/..."
industry	string	Industry	"Software Development"
company_size	string	Employee range	"10,001+ employees"
employee_count	string	Employee count string	"10,001+ employees"
headquarters	string	HQ location	"Redmond, Washington"
company_type	string	Company type	"Public Company"
founded	string	Year founded	"1975"
specialties	string	Specialties list	"Cloud, AI, Enterprise Software"
followers	integer	LinkedIn followers	27657016
recent_posts	array	Last 3 posts	[{text, url, date}]
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "companies",
  "name": "Microsoft",
  "description": "Every company has a mission. What's ours? To empower every person and every organization on the planet to achieve more.",
  "url": "https://www.linkedin.com/company/microsoft",
  "website": "https://www.microsoft.com",
  "logo": "https://media.licdn.com/dms/image/...",
  "industry": "Software Development",
  "company_size": "10,001+ employees",
  "employee_count": "10,001+ employees",
  "headquarters": "Redmond, Washington",
  "company_type": "Public Company",
  "founded": "1975",
  "specialties": "Business Software, Developer Tools, Cloud Computing, AI",
  "followers": 27657016,
  "recent_posts": [
    {
      "text": "We're excited to announce...",
      "url": "https://www.linkedin.com/posts/microsoft_...",
      "date": "2026-02-25"
    }
  ],
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Market research: Analyze companies by industry, size, and location
• B2B targeting: Build company lists for outbound sales campaigns
• Competitor tracking: Monitor competitor companies' follower growth and posts
• Investment research: Screen companies by size, industry, and founding year

Python Example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "companies",
    "urls": [
        "https://www.linkedin.com/company/microsoft",
        "https://www.linkedin.com/company/google"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} — {item['industry']} — {item['followers']} followers")

---

Mode 3: Jobs

Search LinkedIn's public job listings with filters for job type, experience level, time posted, work arrangement, and location.

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"jobs"
searchQuery	string	Yes	Job search keywords	e.g. "software engineer", "data scientist"
location	string	No	Location filter	e.g. "San Francisco", "United States"
maxResults	integer	No	Maximum jobs to return	1–1000, default: 25
timePosted	string	No	Filter by posting date	"24h", "week", "month"
jobType	string	No	Filter by job type	"full-time", "part-time", "contract", "temporary", "volunteer", "internship"
experienceLevel	string	No	Filter by experience	"internship", "entry", "associate", "mid-senior", "director", "executive"
workType	string	No	Filter by work arrangement	"onsite", "remote", "hybrid"
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "jobs",
  "searchQuery": "software engineer",
  "location": "San Francisco",
  "maxResults": 50,
  "jobType": "full-time",
  "experienceLevel": "mid-senior",
  "workType": "remote",
  "timePosted": "week"
}

Output Fields

Field	Type	Description	Example
mode	string	Always "jobs"	"jobs"
job_id	string	LinkedIn job ID	"3847291056"
title	string	Job title	"Senior Software Engineer"
company	string	Company name	"Google"
company_url	string	Company LinkedIn URL	"https://www.linkedin.com/company/google"
location	string	Job location	"San Francisco, CA (Remote)"
posted_date	string	When posted	"2 days ago"
salary	string	Salary range (if listed)	"$180,000 - $250,000"
benefits	string	Benefits info	"Health insurance, 401k"
is_promoted	boolean	Promoted listing	false
url	string	Job listing URL	"https://www.linkedin.com/jobs/view/3847291056"
applicants	string	Number of applicants	"87 applicants"
description	string	Full job description	"We are looking for..."
description_html	string	HTML job description	"<p>We are looking for...</p>"
seniority_level	string	Seniority level	"Mid-Senior level"
employment_type	string	Employment type	"Full-time"
job_function	string	Job function	"Engineering, Information Technology"
industries	string	Industries	"Technology, Software"
company_logo	string	Company logo URL	"https://media.licdn.com/..."
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "jobs",
  "job_id": "3847291056",
  "title": "Senior Software Engineer",
  "company": "Google",
  "company_url": "https://www.linkedin.com/company/google",
  "location": "San Francisco, CA (Remote)",
  "posted_date": "2 days ago",
  "salary": "$180,000 - $250,000",
  "benefits": null,
  "is_promoted": false,
  "url": "https://www.linkedin.com/jobs/view/3847291056",
  "applicants": "87 applicants",
  "description": "We are looking for a Senior Software Engineer to join our Cloud team...",
  "seniority_level": "Mid-Senior level",
  "employment_type": "Full-time",
  "job_function": "Engineering, Information Technology",
  "industries": "Technology, Internet",
  "company_logo": "https://media.licdn.com/dms/image/...",
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Job market analysis: Track hiring trends by role, location, and industry
• Recruiting intelligence: Monitor competitor job postings and salary ranges
• Salary benchmarking: Collect salary data across roles and locations
• Job board aggregation: Feed LinkedIn jobs into your own job board or newsletter

Python Example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "jobs",
    "searchQuery": "data scientist",
    "location": "New York",
    "maxResults": 100,
    "jobType": "full-time",
    "timePosted": "week"
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['title']} at {item['company']} — {item['salary']} — {item['location']}")

---

Mode 4: Posts

Extract posts from LinkedIn profiles and company pages with engagement data (likes, comments, shares).

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"posts"
urls	string[]	Yes	Profile or company URLs	/in/username or /company/name
maxResults	integer	No	Maximum posts to return	1–1000, default: 25
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "posts",
  "urls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/company/microsoft"
  ],
  "maxResults": 20
}

Output Fields

Field	Type	Description	Example
mode	string	Always "posts"	"posts"
author	string	Post author name	"Bill Gates"
author_url	string	Author's LinkedIn URL	"https://www.linkedin.com/in/williamhgates"
text	string	Post content (up to 5000 chars)	"AI is transforming education..."
url	string	Direct post URL	"https://www.linkedin.com/posts/williamhgates_..."
date	string	Publication date	"2026-02-20"
likes	integer	Number of likes/reactions	45000
comments_count	integer	Number of comments	1200
shares_count	integer	Number of shares/reposts	350
media_url	string	Attached image/video URL	"https://media.licdn.com/..."
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "posts",
  "author": "Bill Gates",
  "author_url": "https://www.linkedin.com/in/williamhgates",
  "text": "AI is transforming education in ways we couldn't have imagined...",
  "url": "https://www.linkedin.com/posts/williamhgates_ai-education-technology-activity-123456",
  "date": "2026-02-20",
  "likes": 45000,
  "comments_count": 1200,
  "shares_count": 350,
  "media_url": "https://media.licdn.com/dms/image/...",
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Content analysis: Analyze what topics perform best on LinkedIn
• Social listening: Monitor what companies and influencers are posting about
• Competitive intelligence: Track competitor announcements and messaging
• Influencer research: Identify high-performing content creators in your industry

Python Example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "posts",
    "urls": ["https://www.linkedin.com/in/williamhgates"],
    "maxResults": 10
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['author']}: {item['text'][:100]}... ({item['likes']} likes)")

---

Mode 5: Search

Find LinkedIn profiles by keywords and location using a multi-source search engine: LinkedIn Voyager API for structured data (headline, location) merged with DuckDuckGo, Google, and Bing for real names and clean profile URLs. Automatic fallback chain ensures high reliability — if one source is blocked, the next takes over.

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"search"
searchQuery	string	Yes	Search keywords	e.g. "product manager", "CEO SaaS"
location	string	No	Location filter	e.g. "New York", "London"
maxResults	integer	No	Maximum results to return	1–1000, default: 25
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "search",
  "searchQuery": "product manager",
  "location": "New York",
  "maxResults": 25
}

Output Fields

Field	Type	Description	Example
mode	string	Always "search"	"search"
name	string	Person's name	"Jane Smith"
headline	string	LinkedIn headline	"Product Manager at Stripe"
location	string	Parsed location (when available)	"New York, NY"
image_url	string	Profile photo URL (when available)	"https://media.licdn.com/..."
url	string	LinkedIn profile URL	"https://www.linkedin.com/in/janesmith"
snippet	string	Search result snippet (up to 500 chars)	"Jane Smith is a Product Manager..."
source	string	Data source used	"ddg", "voyager", "google_search", "bing_search"
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "search",
  "name": "Jane Smith",
  "headline": "Product Manager at Stripe",
  "location": "New York, NY",
  "image_url": null,
  "url": "https://www.linkedin.com/in/janesmith",
  "snippet": "Jane Smith is a Product Manager at Stripe with 8+ years of experience in fintech...",
  "source": "ddg",
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Prospecting: Find potential customers by role and location
• Lead discovery: Build targeted outreach lists for sales teams
• Recruiting: Source candidates matching specific criteria
• Market sizing: Estimate the number of professionals in a role/location

Python Example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "search",
    "searchQuery": "CTO SaaS",
    "location": "San Francisco",
    "maxResults": 50
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} — {item['headline']} — {item['url']}")

---

Mode 6: Profile Complete (Premium)

Get everything about a LinkedIn person in one result — full profile data plus their recent posts with engagement metrics (likes, comments, shares). Saves you from running Profiles + Posts separately.

Input Parameters

Parameter	Type	Required	Description	Values
mode	string	Yes	Scraping mode	"profile_complete"
urls	string[]	Yes	LinkedIn profile URLs	linkedin.com/in/username format
maxResults	integer	No	Maximum profiles to return	1–1000, default: 25
proxyConfig	object	No	Proxy settings	Default: Apify RESIDENTIAL
minDelay	integer	No	Min delay between requests (ms)	500–30000, default: 2000
maxDelay	integer	No	Max delay between requests (ms)	1000–60000, default: 5000

Input Example

{
  "mode": "profile_complete",
  "urls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/satyanadella"
  ],
  "maxResults": 10
}

Output Fields

Field	Type	Description	Example
mode	string	Always "profile_complete"	"profile_complete"
name	string	Full name	"Bill Gates"
headline	string	Profile headline	"Co-chair, Bill & Melinda Gates Foundation"
location	string	Location	"Seattle, Washington"
image_url	string	Profile photo URL	"https://media.licdn.com/..."
url	string	Profile URL	"https://www.linkedin.com/in/williamhgates"
current_title	string	Current job title	"Co-chair"
current_company	string	Current employer	"Bill & Melinda Gates Foundation"
connections	integer	Connections count	500
followers	integer	Followers count	35800000
about	string	About section	"Technologist, business leader..."
experience	array	Work history	[{title, company, date_range, duration, location}]
education	array	Education history	[{school, degree, dates}]
posts	array	Up to 10 posts with engagement	[{text, url, date, likes, comments_count, shares_count, media_url}]
posts_count	integer	Number of posts found	5
total_engagement	integer	Sum of all likes + comments + shares	125000
scraped_at	string	ISO timestamp	"2026-02-27T00:00:00.000Z"

Output Example

{
  "mode": "profile_complete",
  "name": "Bill Gates",
  "headline": "Co-chair, Bill & Melinda Gates Foundation",
  "location": "Seattle, Washington, United States",
  "url": "https://www.linkedin.com/in/williamhgates",
  "current_title": "Co-chair",
  "current_company": "Bill & Melinda Gates Foundation",
  "followers": 35800000,
  "experience": [
    {
      "title": "Co-chair",
      "company": "Bill & Melinda Gates Foundation",
      "date_range": "Jan 2000 - Present"
    }
  ],
  "posts": [
    {
      "text": "AI is transforming education in ways we couldn't have imagined...",
      "url": "https://www.linkedin.com/posts/williamhgates_...",
      "date": "2026-02-20",
      "likes": 45000,
      "comments_count": 1200,
      "shares_count": 350,
      "media_url": "https://media.licdn.com/..."
    }
  ],
  "posts_count": 5,
  "total_engagement": 125000,
  "scraped_at": "2026-02-27T00:43:22.000Z"
}

Use Cases

• Influencer analysis: Full profile + content performance in one call
• Sales intelligence: Know who they are AND what they care about
• Recruiting deep-dive: Candidate profile + thought leadership activity
• Competitive intelligence: Track key people + their public messaging

Python Example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("get-leads/linkedin-scraper").call(run_input={
    "mode": "profile_complete",
    "urls": [
        "https://www.linkedin.com/in/williamhgates",
        "https://www.linkedin.com/in/satyanadella"
    ],
    "maxResults": 10
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} — {item['posts_count']} posts — {item['total_engagement']} total engagement")

---

Download Your Data

After every run, download your results in any format:

• JSON — for developers and API integrations
• CSV — for spreadsheets and data analysis
• Excel (XLSX) — for business users
• XML — for data pipelines

Google Sheets: Use =IMPORTDATA() with the CSV download link for instant import.

All Apify export formats available: JSON, JSONL, CSV, XLSX, XML, HTML Table, RSS.

Key Features

• No cookies, no login — 100% safe, zero risk to your LinkedIn account
• 6 modes in one actor — profiles, companies, jobs, posts, search, profile complete
• Chrome TLS fingerprinting — Impit impersonates real Chrome browser fingerprints (JA3/JA4)
• Multi-source search — Voyager API + DuckDuckGo + Google + Bing fallback chain for maximum reliability
• Residential proxy rotation — automatic IP rotation with retry on blocks
• Human-like behavior — randomized delays with Box-Muller normal distribution
• 256 MB memory — lightweight HTTP-only architecture, minimal compute costs
• MCP-compatible — works with Claude, GPT, Cursor, and any MCP client
• Pay per result — no subscription, no monthly fee

Limitations

• Profile data is limited to what LinkedIn shows on public pages
• Some profiles may be behind a login wall (the actor will still extract available data)
• Post engagement metrics may be approximate
• Search mode uses a multi-source fallback chain (Voyager API + DDG + Google + Bing) for high reliability. Field completion: ~100% names, ~94% headlines, ~54% locations

FAQ

Do I need a LinkedIn account? No. This scraper works without any LinkedIn cookies or login. Your LinkedIn account stays safe.

How fast is it? Profiles: ~3-5 seconds each. Jobs: ~25 seconds per 20 listings (with detail enrichment). Search: ~7-10 seconds for 10 results (multi-source merge).

What if I get blocked? Automatic retry with proxy rotation (up to 3 attempts per request). Residential proxies are required.

Can I scrape thousands of results? Yes. Set maxResults up to 1,000. The scraper handles pagination, deduplication, and rate limiting automatically.

Is there a monthly subscription? No. Pay only for results delivered, starting at $1/1K for jobs.

Support

Questions or feedback? Contact us at get-leads@apify.com

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