Command Palette

Search for a command to run...

UnylyUnyly
Весь каталог

Job Recommender System With

БесплатноНе проверен

You said: how to activate uv env ChatGPT said: uv is a fast Python package manager and virtual environment tool (alternative to pip + venv). To activate a uv en

GitHubEmbed

Описание

You said: how to activate uv env ChatGPT said: uv is a fast Python package manager and virtual environment tool (alternative to pip + venv). To activate a uv environment, follow these steps: Step 1: Create a virtual environment using uv Open terminal in

README

Python Streamlit Groq Apify MCP

Upload your resume and get AI-powered job recommendations, skill gap analysis, and a personalized career roadmap --- powered by Groq LLaMA 3.3-70B and real-time job listings from LinkedIn & Naukri via Apify.

🔗 Live Demo:
https://chitaki10-job-recommender-system-with-mcp-app-eynbly.streamlit.app


Table of contents

  • Features
  • Architecture
  • Tech Stack
  • Getting Started
  • API Keys Setup
  • MCP Tool Server
  • Project Structure
  • Results
  • License

Features

  • Resume Parsing --- Extracts raw text from uploaded PDF résumés
using PyMuPDF\
  • Resume Summary --- LLM summarizes your skills, experience, and
profile in seconds\
  • Skill Gap Analysis --- Identifies missing skills, certifications,
and areas to improve\
  • Career Roadmap --- Personalized 6--12 month plan: skills to
learn, projects to build, certs to pursue\
  • Real-Time Job Recommendations --- Fetches live jobs from LinkedIn
and Naukri via Apify API\
  • MCP Tool Server --- Core functions exposed as MCP tools

Architecture

user uploads Résumé (PDF)
│
▼
Extract PDF Text (PyMuPDF)
│
▼
Groq LLaMA 3.3-70B (LLM)
│
├── Summary
├── Skill Gap
├── Career Roadmap
└── Job Keywords
│
├──────────────┬───────────────┐
▼              ▼
LinkedIn Jobs  Naukri Jobs
(Apify Actor)  (Apify Actor)
│
└──────────────┬───────────────┘
▼
Job Recommendations UI

Tech Stack

Component Technology


UI Streamlit LLM Groq API --- llama-3.3-70b-versatile PDF Parsing PyMuPDF Job Scraping Apify MCP Server mcp Python SDK Package Manager uv Deployment Streamlit Cloud


Getting Started

clone Repository

git clone https://github.com/chitaki10/Job_Recommender_System_with_MCP.git
cd Job_Recommender_System_with_MCP

Install Dependencies

uv venv
uv add -r requirements.txt

Create .env file

GROQ_API_KEY=your_groq_api_key_here
APIFY_API_TOKEN=your_apify_api_token_here

Run App

uv run streamlit run app.py

MCP Tool Server

Run MCP server:

uv run python mcp_server.py

Test with inspector:

npx @modelcontextprotocol/inspector uv run python mcp_server.py

Available tools:

  • extract_text_from_pdf
  • ask_groq
  • fetch_linkedin_jobs
  • fetch_naukri_jobs

Project Structure

Job_Recommender_System_with_MCP/
│
├── app.py
├── mcp_server.py
├── requirements.txt
├── pyproject.toml
├── .env
├── .gitignore
│
└── src/
    ├── __init__.py
    └── helper.py

Results

  • Resume summary generated in seconds\
  • Skill gap analysis provided\
  • Career roadmap generated\
  • 120 real-time jobs fetched


Contact

GitHub: https://github.com/chitaki10 [email protected]

from github.com/chitaki10/Job_Recommender_System_with_MCP

Установка Job Recommender System With

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/chitaki10/Job_Recommender_System_with_MCP

FAQ

Job Recommender System With MCP бесплатный?

Да, Job Recommender System With MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Job Recommender System With?

Нет, Job Recommender System With работает без API-ключей и переменных окружения.

Job Recommender System With — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Job Recommender System With в Claude Desktop, Claude Code или Cursor?

Открой Job Recommender System With на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

Похожие MCP

Compare Job Recommender System With with

Не уверен что выбрать?

Найди свой стек за 60 секунд

Автор?

Embed-бейдж для README

Похожее

Все в категории development