🔥Advanced node.js package for getting job listings from LinkedIn 💼

A Model Context Protocol (MCP) server that provides tools to interact with LinkedIn's Feeds and Job API.

Extract LinkedIn data with the #1 LinkedIn Scraper API, including profiles, job postings, company details, connections, and posts. Start your free trial now!

An unofficial API to fetch job listings from LinkedIn. This API allows you to search for jobs using keywords, location, and date filters.

Python script to extract data of Linkedin job openings using Selenium and BeautifulSoup. Storing the data using Google Sheets API.

It is a 3 tier distributed web application simulating linkedin. It is built solely using MERN Stack. It is a single point of access for both applicants and recruiters. Recruiters can post their jobs and the applicants can apply to these jobs.The overall project involved the set of tasks as mentioned below: - Creation of React.js pages for users. - Managing state of application frontend using Redux. - Creating client-side REST API calls. - Using Kafka to break down the features into individual blocks that can be accessed individually making the application more scalable. - Managing REST API calls from clients using NodeJS at the server side. - Redis Caching for improving the response time of application. - Database sharding and replication to make application scalable and reliable. - Maintaining user sessions. - Managing and storing data to MongoDB, through REST APIs. Technology stack: Kafka, Node.js, React.js, Redux, MongoDB, MySQL, AWS Docker, Bootstrap.

AI-powered job matching system that automatically fetches jobs from LinkedIn & SEEK, matches them against your resume using Google's Gemini API, and enriches results with Glassdoor company insights.

API to scrap jobs from various web sites i.e; LinkedIn, Glassdoor, indeed, google, bayt, zip_recruiter and Naukri according to the parameters like hours old, country, city and so on via API endpoint. Connected with MongoDB as well for logging while maintaining pylint score 10/10.

This repository contains a project that automates the process of scraping LinkedIn profiles of recruiters, HR personnel, and hiring managers to collect relevant data such as email addresses. Using this data, the project leverages OpenAI’s API to generate customized emails based on the company’s needs, job openings, and other factors.

Scrapping linkedin job posts and filtering them using OpenAI API

The latest and most advanced LinkedIn Job Scraper. Our LinkedIn Jobs Scraper extracts real-time job postings at scale from all over the world. A new research tool built for recruitment, insights and HR.

Built an automated code job boards scraper (Indeed, Glassdoor, Linkedin, Monster) that gets job postings and uses the company websites with Apollo’s API to generate a set of people leads, with full Linkedin, emails, and phones for outreach.

A Python tool that automates LinkedIn job search, ranking, and export by combining Bright Data's LinkedIn Job Listings API with OpenAI-powered AI job matching and scoring.

An idea to identify the companies that provide H1B sponsorship to international employees. Using governmental data for the past decade to analyze the companies, skills and job roles required to increase the chance for obtaining H1B visa sponsorships. This API can be added as an extension to companies like LinkedIn in their “Job Search” Section.

This Django job portal scrapes Django job listings from Indeed and LinkedIn with Selenium, simplifying job searches. It provides a RESTful API for accessing job data.

unofficial linkedin api for finding jobs and searching for/connecting with users

Automating the Process of Searching for Jobs using the Selenium Open-Source API through 4 Major Job Sites (Indeed, Glassdoor, Linkedin, IrishJobs)

Automated daily job search pipeline — aggregates company tracking, sends styled HTML email digests, tailors resumes with Gemini AI, drafts LinkedIn outreach messages, and scans remote job APIs for given location. Hot jobs for the given role and many features are made as claude skills too newly.

An AI-powered tool that compares resumes with job descriptions to generate fit scores, resume suggestions, and interview questions using OpenAI, LangChain, Resume Parser, and the LinkedIn API.

This whatsapp helps you to invoke everyone in the group, with additional functionalities like downloading a youtube video or answering your queries.

# Trybe This repository contains all the learning activities developed by João V.S Dias https://www.linkedin.com/in/diasvictorj/_ while studying at [Trybe](https://www.betrybe.com/) :rocket: _"Trybe is a school of the future for anyone who wants to improve their life and build a successful career in technology, where people only pay when they get a good job."_ The program has more than 1,500 hours of classroom and online classes, covers an introduction to software development, front-end, back-end, computer science, software engineering, agile methodologies and behavioral skills. ## Web Development Fundamentals :white_check_mark: ##### Block 1: Introduction - Unix & Shell - [ ] 1-3: _Unix & Shell- Part 1_ - [ ] 1-4: _Unix & Shell- Part 2_ ##### Block 2: Git & GitHub - [ ] 2-1: _What is it and what is it for?_ - [ ] 2-2: _Understanding the commands_ - [ ] 2-3: _Internet - Understanding how it works_ ##### Block 3: Introduction - HTML & CSS - [ ] 3-1: _HTML & CSS - Page Structures_ - [ ] 3-2: _HTML & CSS - Getting Started with CSS_ - [ ] 3-3: _HTML & CSS - Selectors and positioning_ - [ ] 3-4: _Semantic HTML_ - [ ] 3-5: _[Project - HTML & CSS]()_ ##### Block 4: Introduction - JavaScript - [ ] 4-1: _JavaScript - First steps_ - [ ] 4-2: _JavaScript - Array and For_ loop - [ ] 4-3: _JavaScript - Programming Logic and Algorithms_ - [ ] 4-4: _JavaScript - Objects and Functions_ - [ ] 4-5: _[Project - Playground Functions]()_ ##### Block 5: Introduction - JavaScript - Projects - [ ] 5-1: _JavaScript - DOM and selectors_ - [ ] 5-2: _JavaScript - Working with elements_ - [ ] 5-3: _JavaScript - Events_ - [ ] 5-4: _JavaScript - Web Storage_ - [ ] 5-5: _[Project - Meme Generator]()_ - [ ] 5-6: _[Project - Pixel Art]()_ - [ ] 5-7: _[Project - Task List]()_ - [ ] 5-7: _[Project - Guess the Color]()_ - [ ] 5-7: _[Project - Mysterious Letter]()_ ##### Block 6: Advanced HTML & CSS - [ ] 6-1: _HTML & CSS - Forms_ - [ ] 6-2: _JavaScript Libraries and CSS Frameworks_ - [ ] 6-3: _CSS Flexbox - Part 1_ - [ ] 6-4: _CSS Flexbox - Part 2_ - [ ] 6-5: _CSS Responsive - Mobile First_ - [ ] 6-6: _[Project - Facebook homepage]()_ ##### Block 7: JavaScript ES6 & Unit Tests - [ ] 7-1: _JavaScript ES6 - let, const, arrow functions and template literals_ - [ ] 7-2: _JavaScript ES6 - Objects_ - [ ] 7-3: _Unit tests in JavaScript_ - [ ] 7-4: _[Project - JavaScript Unit Tests]()_ ##### Block 8: JavaScript ES6 - [ ] 8-1: _JavaScript ES6 - Higher Order Functions - forEach, find, some, every, sort_ - [ ] 8-2: _JavaScript ES6 - Higher Order Functions - map and filter_ - [ ] 8-3: _JavaScript ES6 - Higher Order Functions - reduce_ - [ ] 8-4: _JavaScript ES6 - spread operator, rest parameter, destructuring and more_ - [ ] 8-5: _[Project - Zoo functions]()_ ##### Block 9: Asynchronicity & Callbacks - [ ] 9-1: _Asynchronous JavaScript and Callbacks_ - [ ] 9-2: _JavaScript Promises_ - [ ] 9-3: _[Project - Shopping Cart]()_ ##### Block 10: Jest - [ ] 10-1: _First steps in Jest_ - [ ] 10-2: _Jest - Asynchronous Tests_ - [ ] 10-3: _Jest - Simulating behavior_ - [ ] 10-4: _[Project - Asynchronous Jest and Mocking]()_ ## Front-end development :hourglass_flowing_sand: ##### Block 11: Introduction - React - [ ] 11-1: _'Hello, world!' on React!_ - [ ] 11-2: _React Components_ - [ ] 11-3: _[Project - Movie Cards Library]()_ ##### Block 12: React - [ ] 12-1: _Components with status_ - [ ] 12-2: _Events and forms in React_ - [ ] 12-3: _[Project - Movie Cards Library Stateful]()_ ##### Block 13: React - [ ] 13-1: _Improving component reuse: props.children and PropTypes_ - [ ] 13-2: _Component lifecycle in React_ - [ ] 13-3: _React Router_ - [ ] 13-4: _[Project - Movie Cards Library CRUD]()_ ##### Block 14: Agile Methodologies - [ ] 14-1: _Agile Methodologies_ - [ ] 14-2: _[Project - Frontend Online Store]()_ ##### Block 15: Tests in React - [ ] 15-1: _Testing React with the React Testing Library_ - [ ] 15-2: _Testing React with the React Testing Library - Part 2_ - [ ] 15-3: _[Project - Tests in React]()_ ##### Block 16: Introduction to Redux - [ ] 16-1: _Introduction to Redux_ - [ ] 16-2: _React with Redux - Part 1_ - [ ] 16-3: _React with Redux - Practice_ - [ ] 16-4: _React with Redux - Part 2_ - [ ] 16-5: _Synchronous tests with React-Redux_ - [ ] 16-6: _[Project - Table with data filters]()_ ##### Block 17: Project React - [ ] 17-1: _[Project - Trivia Game]()_ ##### Block 18: React & Context API - [ ] 18-1: _Context API of React_ - [ ] 18-2: _React Hooks - useState and useContext_ - [ ] 18-3: _React Hooks - useEffect and Custom Hooks_ - [ ] 18-4: _[Project - StarWars Datatable with Context API and Hooks]()_ ##### Block 19: Front-end Final Project - [ ] 19-1: _[Project - Recipe App]()_ ## Back-end Development :hourglass_flowing_sand: ##### Block 20: Introduction - Relational Databases - [ ] 20-1: _SQL Database_ - [ ] 20-2: _Finding data in a database_ - [ ] 20-3: _Filtering data specifically_ - [ ] 20-4: _Manipulating tables_ - [ ] 20-5: _[Project - All For One]()_ ##### Block 21: Relational Databases - [ ] 21-1: _Most used functions in SQL_ - [ ] 21-2: _Uncomplicating JOINs and UNIONs_ - [ ] 21-3: _Stored Routines & Subqueries_ - [ ] 21-4: _[Project - Vocabulary Booster]()_ ##### Block 22: Relational Databases - [ ] 22-1: _Transforming ideas into a database model_ - [ ] 22-2: _Normalization, Normal Forms and Dumps_ - [ ] 22-2: _Turning ideas into a database model - Part 2_ - [ ] 22-3: _[Project - One For All]()_ ##### Block 23: Introduction - NoSQL - [ ] 23-1: _MongoDB - Introduction_ - [ ] 23-2: _Filter Operators_ - [ ] 23-3: _[Project - Date Flights]()_ ##### Block 24: Updates - [ ] 24-1: _Simple Updates_ - [ ] 24-2: _Complex Updates - Arrays - Part 1_ - [ ] 24-3: _Complex Updates - Arrays - Part 2_ - [ ] 24-4: _[Project - Commerce]()_ ##### Block 25: Aggregation Framework - [ ] 25-1: _Aggregation Framework - Part 1_ - [ ] 25-2: _Aggregation Framework - Part 2_ - [ ] 25-3: _[Project - Aggregations]()_ ##### Block 26: Intro - NodeJS - [ ] 26-1: _NodeJS - Introduction_ - [ ] 26-2: _NodeJS - Asynchronous Flow_ - [ ] 26-3: _NodeJS - Architecture_ - [ ] 26-4: _[Project - A CLI of Ice and Fire]()_ ##### Block 27: NodeJS - [ ] 27-1: _Express: HTTP with Node.js_ - [ ] 27-2: _Software Architecture - Introduction to MVC_ - [ ] 27-3: _[Project - Cookmaster]()_ ##### Block 28: NodeJS - [ ] 28-1: _Software Architecture - Service Layer_ - [ ] 28-2: _Web Architecture - Rest and Restful_ - [ ] 28-3: _[Project - Store Manager]()_ ##### Block 29: NodeJS - [ ] 29-1: _NodeJS - JWT - (JSON Web Token)_ - [ ] 29-2: _NodeJS - Upload files with Multer_ - [ ] 29-3: _[Project - Cookmaster V2]()_ ##### Block 30: Introduction - Deploy - [ ] 30-1: _Infrastructure - Deploy with Heroku_ - [ ] 30-2: _Deploy - Process Managers_ - [ ] 30-3: _[Project - Stranger Things]()_ ##### Block 31: Project - [ ] 31-1: _[Project - Trybeer]()_ ##### Block 32: Software Architecture - [ ] 32-1: _Architecture - SOLID Principles_ - [ ] 32-2: _ORM - Application interface with the database_ - [ ] 32-3: _Software Architecture - DDD_ - [ ] 32-4: _Good practice writing tests_ - [ ] 32-3: _[Project - Blogs API]()_ ##### Block 33: Sockets - [ ] 30-1: _Sockets - TCP/UDP & NET_ - [ ] 30-2: _Sockets - Socket.io_ - [ ] 30-3: _[Project - Webchat]()_ ##### Block 34: Project - [ ] 34-1: _[Project - Trybeer V2]()_ ## Computer Science :hourglass_flowing_sand: ##### Block 35: Introduction - Computer Science - [ ] 35-1: _Computer Architecture_ - [ ] 35-2: _Network architecture_ - [ ] 35-3: _Computer networks, tools and security_ - [ ] 35-4: _[Project - Exploring the protocols]()_ ##### Block 36: Python - [ ] 35-1: _Learning Python_ - [ ] 35-2: _Tests and Exceptions_ - [ ] 35-3: _Data Input and Output_ - [ ] 36-4: _Data Input and Output_ - [ ] 35-5: _[Project - Tech news]()_ # [...]

dokcer image with api to scrape jobs from Linkedin

An API to retrieve jobs from LinkedIn, using Flask and Google Custom Search Engine (GCSE)

This web application uses generative AI models, together with the LinkedIn and SERP API to make tailored job suggestions

OpenRecruit is a Job Searching App that fetches jobs from various platforms like LinkedIn, Indeed, ZipRecruiter, and others on Google for Jobs in real-time using JSearch Api. This app is built using React Native and Expo. This app is my first project in React Native.

Chrome extension that automates LinkedIn job searches. It auto-scrolls job listings, filters for relevant positions, removes duplicates, and uses OpenAI API to intelligently match jobs to your criteria. Filtered results are exported directly to Google Sheets for easy review and sharing

Automated job hunting pipeline — collects listings from LinkedIn, Indeed, Glassdoor & Gupy, filters them with AI (Claude API), and sends daily notifications via email or Discord.

Built a Prototype Of LinkedIn which replicates each functionality from job posting, job applying to messaging inbox and connections using AWS, MERN stack, JavaScript, MySQL, Redux, REST API, Kafka, RDS, Redis Cache, S3, JWT.

LinkedIn Clone made with C# where users can register as job seekers or recruiters. Friends system, messaging, users can apply to job postings and recruiters can approve/deny applications. 3rd party APIs for stock prices and tech news on the front page.

🤖 AI-Powered LinkedIn Scraper | Extract Emails & Profiles Ethically with Python + Selenium ✅ Bypasses LinkedIn restrictions with human-like behavior ✅ Enriches data using OpenAI API (job titles, company info) ✅ Exports to CSV/Google Sheets for CRM integration ✅ Anti-detection techniques (random delays, user-agent rotation)