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URL: https://apify.com/worldunboxer/rapid-linkedin-scraper

⇱ Rapid Linkedin Jobs Scraper | LinkedIn Jobs API Β· Apify


πŸ‘ ⚑️Rapid Linkedin Jobs Scraper avatar

⚑️Rapid Linkedin Jobs Scraper

Pricing

from $0.75 / 1,000 results

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⚑️Rapid Linkedin Jobs Scraper

LinkedIn job scraper tool to extract job listings, company, and complete job information instantly. Scrape LinkedIn jobs by keywords, city ,country, or company. Get structured data including titles, descriptions, salaries, requirements, and employer info. Fast, efficient job data extraction.

Pricing

from $0.75 / 1,000 results

Rating

3.6

(22)

Developer

πŸ‘ Umesh Patidar

Umesh Patidar

Maintained by Community

Actor stats

126

Bookmarked

12K

Total users

994

Monthly active users

2.8 days

Issues response

a day ago

Last modified

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πŸš€ Rapid LinkedIn Scraper (No Login) - Fast & Accurate Job Scraping

πŸ‘ Output
πŸ‘ Success Rate
πŸ‘ Connect with MCP

πŸ‘ Hero Image

Welcome to the Rapid LinkedIn Scraper! This powerful and user-friendly web scraping tool is designed to extract LinkedIn job listings effortlesslyβ€”without requiring login credentials. Whether you are building a job board, conducting market research, or performing data analysis, this API provides highly structured, accurate, and real-time job data extraction.

πŸ“‘ Table of Contents


🌟 Why Use Rapid LinkedIn Scraper?

βœ… No Login Required – Avoid the hassle of credentials, CAPTCHAs, and LinkedIn account bans. βœ… Blazing Fast & Cost-Effective – Designed for high-speed web scraping and minimal compute usage on the Apify platform. βœ… Highly Customizable Filters – Target jobs precisely by title, location, job type, experience level, and posting time. βœ… Rich Data Extraction – Get detailed payload information including salaries, company logos, full raw HTML descriptions, and applicant counts. βœ… Seamless Integration – Clean, structured output in JSON, CSV, XML, Excel, HTML Table, RSS, and JSONL formats ready for APIs, databases, or analytics dashboards.


⚑ Quick Start

Get your job data in three simple steps using the Apify platform:

  1. Go to the Actor page on Apify.
  2. Fill in the inputs (e.g., Job Title: "Software Engineer", Location: "Remote").
  3. Click "Start" and wait for the run to finish.
  4. Download the data in JSON, CSV, XML, Excel, HTML Table, RSS, or JSONL format.

πŸ’» Programmatic Integration (API)

If you want to integrate the scraper directly into your database, app, or automation pipeline, you can use the Apify API.

Node.js Example

import{ ApifyClient }from'apify-client';
// Initialize the ApifyClient with your API token
const client =newApifyClient({
token:'YOUR_APIFY_API_TOKEN',
});
// Prepare actor input
const input ={
"job_title":"Software Engineer",
"location":"Remote",
"jobs_entries":10,
"posted_within":"Past 24 hours"
};
(async()=>{
// Run the actor and wait for it to finish
const run =await client.actor("worldunboxer/rapid-linkedin-scraper").call(input);
// Fetch and print actor results from the run's dataset (if any)
const{ items }=await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
})();

Python Example

from apify_client import ApifyClient
# Initialize the ApifyClient with your API token
client = ApifyClient("YOUR_APIFY_API_TOKEN")
# Prepare the Actor input
run_input ={
"job_title":"Software Engineer",
"location":"Remote",
"jobs_entries":10,
"posted_within":"Past 24 hours"
}
# Run the Actor and wait for it to finish
run = client.actor("worldunboxer/rapid-linkedin-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)

πŸ€– AI Use Cases & Agent Integrations (Apify MCP)

Supercharge your AI agents with real-time job data! You can directly connect this scraper to your favorite AI models and environments using the Model Context Protocol (MCP). Let your AI assistants query real-world job market data dynamically.

πŸ”— MCP Configurator URL for Rapid LinkedIn Scraper

Connect seamlessly with these powerful AI agents:

  • Claude Desktop
  • Claude.ai
  • Claude Code
  • Antigravity
  • Cursor
  • ChatGPT
  • Codex CLI
  • VS Code
  • Kiro
  • Others (Any MCP-compatible client)

πŸ“₯ Input Parameters

Customize your scraping tasks using these supported input fields.

TitleIDDescription
Job Titlejob_titleThe job role to search for (e.g., "Python Developer", "Data Scientist").
LocationlocationTarget region or location (e.g., "New York", "Remote").
Number of Jobs Entriesjobs_entriesMaximum number of job listings to scrape per run.
Start Offsetstart_jobsPagination offset (skip the first N jobs). Default is 0.
Company Namescompany_namesList of specific companies to filter jobs by.
CitiescitiesList of specific cities to filter the search results.
Experience Levelexperience_levelRequired experience: Intern, Assistant, Junior, Mid-Senior, Director, Executive.
Employment Typeemployment_typeJob type: Full-time, Part-time, Contract, Temporary, Volunteer, Internship, Other.
Work Arrangementwork_arrangementLocation type: On-site, Remote, Hybrid.
Job Posting Timeposted_withinTimeframe: Any Time, Past 24 hours, Past Week, Past Month.
Custom Job Posting Timejob_post_timeCustom time range string if predefined posted_within options aren't used.
Easy Apply Onlyeasy_applySet to true to scrape only jobs that have the "Easy Apply" option.

🎯 Actor Input Example

πŸ‘ Rapid LinkedIn Scraper Input Example
πŸ‘ Rapid LinkedIn Scraper Input Example


πŸ“€ Output Format

The scraper returns clean, structured data for every job listing.

TitleIDDescription
Job IDjob_idUnique LinkedIn identifier for the job post.
Job URLjob_urlDirect link to the LinkedIn job posting.
Apply URLapply_urlExternal URL to apply for the job, or the LinkedIn page if Easy Apply.
Job Titlejob_titleTitle of the position.
Company Namecompany_nameName of the hiring company.
Company URLcompany_urlLink to the company's LinkedIn profile.
Company Logo URLcompany_logo_urlDirect URL to the company's logo image.
LocationlocationGeographic location of the job.
Time Postedtime_postedRelative time since the job was posted (e.g., "2 days ago").
Number of Applicantsnum_applicantsCurrent number of applicants for the position.
Salary Rangesalary_rangeProvided salary or compensation details.
Job Descriptionjob_descriptionPlain text of the full job description.
Job Description HTMLjob_description_raw_htmlFull job description in raw HTML format.
Seniority Levelseniority_levelListed seniority level required for the job.
Employment Typeemployment_typeEmployment type categorization.
Job Functionjob_functionCore functions associated with the role.
IndustriesindustriesThe business industries related to the job.
Easy Applyeasy_applyBoolean flag indicating if LinkedIn Easy Apply is available.

🎯 Job Data Output Example

πŸ‘ Rapid LinkedIn Scraper Data Output


❓ Frequently Asked Questions (FAQ)

Q: Do I need a LinkedIn account to use this scraper? A: No! The Rapid LinkedIn Scraper is designed to bypass the need for a login, ensuring your personal account remains safe from bans or restrictions.

Q: Is it legal to scrape LinkedIn jobs? A: Web scraping public data (like public job postings) is generally permissible for educational and research purposes. However, you should always review LinkedIn's Terms of Service and consult legal counsel regarding your specific use case.

Q: Can I integrate this with my own database or app? A: Absolutely. The output is provided in clean JSON, CSV, XML, Excel, HTML Table, RSS, and JSONL formats and can be accessed programmatically via the Apify API, making database ingestion seamless.

Q: How fast is the scraper? A: The scraper is highly optimized for speed, relying on efficient network requests rather than heavy browser automation, allowing you to extract hundreds of jobs in seconds.


Legal & Disclaimer

  • This tool is intended for educational and research purposes only.
  • Respect LinkedIn's terms of service while scraping data.
  • The author is not responsible for misuse of this scraper.

Contact & Support

For support, feedback, or custom requests, feel free to reach out: Feedback Form: https://forms.gle/HQyJGukRrCKmf2qF8<br> Email: umeshpatidar.dev@gmail.com<br> LinkedIn: Umesh Patidar

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