Naukri MCP Server

Naukri MCP Server

Enables job searching on Naukri via MCP, offering tools like search_jobs, get_job_details, get_trending_roles, and get_my_profile_summary, currently using demo data.

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README

Naukri MCP Server šŸš€

A Python MCP (Model Context Protocol) server that provides job-search tools, designed to connect with Gemini Spark as a custom Connected App.

Architecture

Gemini Spark (gemini.google.com)
       │
       │  MCP protocol over HTTP
       ā–¼
Your MCP Server (deployed on Render)
       │
       │  (future: scraping / API)
       ā–¼
   Naukri.com

Available Tools

Tool Description
search_jobs Search for job listings by role, location, and experience level
get_job_details Get detailed information about a specific job
get_trending_roles See trending/in-demand roles in a city
get_my_profile_summary View your Naukri profile summary

Note: Currently uses demo data. Real Naukri integration can be added later.


Quick Start (Local)

1. Create a virtual environment

python -m venv venv

# Windows
venv\Scripts\activate

# macOS/Linux
source venv/bin/activate

2. Install dependencies

pip install -r requirements.txt

3. Run the server

python server.py

The server starts at: http://localhost:8000/mcp

4. Test with the MCP CLI (optional)

# In a separate terminal
mcp client http://localhost:8000/mcp

Then try calling a tool:

> call search_jobs {"query": "Data Analyst", "location": "Chennai"}

Deploy to Render

Option A: One-click deploy (Blueprint)

  1. Push this repo to GitHub
  2. Go to Render Dashboard → New → Blueprint
  3. Connect your GitHub repo
  4. Render will detect render.yaml and set everything up automatically
  5. Your MCP URL will be: https://naukri-mcp-server.onrender.com/mcp

Option B: Manual setup

  1. Push this repo to GitHub
  2. Go to Render Dashboard → New → Web Service
  3. Connect your GitHub repo
  4. Configure:
    • Build Command: pip install -r requirements.txt
    • Start Command: python server.py
    • Plan: Free
  5. Deploy!

āš ļø Free tier services spin down after inactivity. The first request after idle may take ~30 seconds.


Connect to Gemini Spark

Once deployed, connect your MCP server to Gemini:

  1. Open gemini.google.com on a computer
  2. Go to Settings → Connected Apps (or Personal Intelligence)
  3. Look for "Custom apps for Spark" or "Other apps"
  4. Click "Add a custom app"
  5. Enter:
    • Name: Naukri Job Search
    • MCP Server URL: https://naukri-mcp-server.onrender.com/mcp
  6. Save and start chatting!

Example prompts

"Find Data Analyst jobs in Chennai for freshers"

"What are the trending tech roles in Bangalore right now?"

"Show me details for job JOB-123456"

"Review my Naukri profile and suggest improvements"


Project Structure

naukri_mcp/
ā”œā”€ā”€ server.py            # Main MCP server with tools
ā”œā”€ā”€ requirements.txt     # Python dependencies
ā”œā”€ā”€ Procfile             # Start command for Render
ā”œā”€ā”€ render.yaml          # Render deployment blueprint
ā”œā”€ā”€ .gitignore           # Git ignore rules
└── README.md            # This file

Tech Stack

  • MCP Python SDK — FastMCP with Streamable HTTP transport
  • Render — Free-tier cloud deployment
  • Python 3.12+

Roadmap

  • [x] Demo MCP server with mock data
  • [ ] Real Naukri job search (web scraping)
  • [ ] Profile sync from Naukri
  • [ ] Job application tracking
  • [ ] Resume analysis tool
  • [ ] Interview prep tool

License

MIT

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