Naukri Jobs Scraper

Collect public Naukri India job listings by keyword, location, or Naukri search/job URL. Export titles, companies, locations, salary and experience text, skills, and available descriptions to JSON, CSV, or Excel.

This Actor is for recruiting research and job-market datasets. Despite the historical slug, NaukriGulf is not supported. Experience/date filters and automatic change tracking are not supported in the current build.

Quick start

1. Enter a role in Keywords, such as software engineer, and a Location, such as Bangalore.
2. Start with Maximum jobs set to 5. Keep Include descriptions enabled if you need available description text.
3. Run the Actor, open its dataset, and export the results.

{
  "site": "naukri",
  "keywords": ["software engineer"],
  "location": "Bangalore",
  "maxItems": 5,
  "includeDescription": true
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

• Scrape Naukri backend developer jobs in Bangalore
• Scrape Naukri data analyst jobs in Bangalore
• Scrape Naukri software engineer jobs in Bangalore

What you get

One public Naukri India job row with its source link, available title, employer, location, salary and experience text. Skills can be empty and enabled descriptions can still be short or unavailable. Observation timestamps and the constant new label describe this run rather than changes against previous exports.

Who is it for?

• Recruiting researchers reviewing public India job samples by role and location.
• Hiring-market analysts keeping source-reported salary and experience text for their own research.
• Job-data developers importing source-linked listings and optional descriptions.
• Workforce reporting teams joining their own retained exports without assuming built-in tracking.

How you can use the data

• Review a Bangalore software-engineer sample. Use the existing Naukri India query and five-job cap with descriptions enabled. Keep jobUrl, title, companyName and available skills together before checking the public job itself.
• Compare related role samples yourself. Use the existing backend-developer and data-analyst examples for Bangalore with small caps. Keep salary and experience as source text rather than inferred numeric ranges, normalized dates or guaranteed eligibility.
• Keep URL-only and generated searches distinct. For a known keyword/location path URL, clear keywords and location to avoid adding a generated general-location search. Supplied URLs and generated sources are otherwise additive, and arbitrary browser filters are not reproduced.
• Join repeat exports in your own reporting. Keep jobId or jobUrl and collection timestamps in your destination. Constant changeType new and this-run firstSeenAt do not establish a new posting or change since a previous run. Scoring, alerts and historical comparison are downstream work.

Input settings

Setting	JSON key	Behavior
Job site	site	Naukri India only. Default naukri.
Keywords	keywords	List of roles or skills. The form prefills software engineer. API calls must supply their own keywords.
Location	location	Location for generated searches. Form/schema default Bangalore. A location alone generates a general jobs search.
Start URLs	startUrls	Public Naukri URLs, processed in addition to generated searches. Use keyword/location path URLs such as /software-engineer-jobs-in-bangalore. Arbitrary URL filters are not preserved.
Maximum jobs	maxItems	Global saved-row limit, default 20, maximum 5000. Not a promise that this many jobs exist.
Include descriptions	includeDescription	Default true. Available plain-text description, not guaranteed full job content.
Proxy configuration	proxyConfiguration	Existing proxy settings. See field help for defaults and custom settings.

For a URL-only run, explicitly set keywords: [] and location: "" to avoid adding a generated location search. URLs may be strings or objects containing url. At least one usable Naukri URL, keyword, or location is needed. Results are processed in input/source order, not sorted by date or salary.

The advanced experienceMin, experienceMax, and changedSince fields do not provide reliable experience filtering or incremental extraction. Do not use them to select only new jobs. The hidden maxJobs alias, when provided, takes precedence over maxItems.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Each dataset row represents a job listing. Missing source values are generally null. Skills default to an empty list. A description can be absent even when enabled.

Illustrative shape only, not a captured job record:

{
  "source": "naukri",
  "jobUrl": "https://www.naukri.com/job-listings-example",
  "jobId": null,
  "title": "Illustrative job title",
  "companyName": null,
  "location": null,
  "salary": null,
  "skills": [],
  "description": null,
  "changeType": "new"
}

Fields	Meaning
source, searchUrl, jobUrl, jobId	Source board, originating search when applicable, listing URL, and available identifier.
title, companyName, companyUrl, location	Job and employer information supplied by the source.
postedAt, experience, salary	Source text, not normalized dates or numeric salary/experience ranges.
employmentType, workMode, education	Optional source labels. Work-mode values may be source codes rather than readable remote/hybrid labels.
skills, description, industry, functionArea	Available skills, description text, and classification. Description length is limited and may be a short listing excerpt.
applyUrl	Available apply link, otherwise the job URL. Not a completed application or guaranteed external application form.
firstSeenAt, lastSeenAt, scrapedAt	Observation timestamps within this run, not persisted cross-run history.
changeType	Currently new for every emitted row. Not a comparison with earlier runs.

On successful completion, RUN-SUMMARY in key-value storage includes saved count, queued-page count, and any work skipped near the run deadline. It is not a per-input coverage report or a guaranteed record after a failed run.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The start event is charged once after input preparation and can apply even if no jobs are returned. The item event applies to each saved job. No paid error or status rows are saved.

Use a small input and explicit global row cap. See the live Pricing tab for current rates and plan discounts. The row cap does not limit requests or elapsed time.

Tips for best results

• Choose Naukri India explicitly. The historical slug does not mean NaukriGulf is supported.
• Clear keywords and location for URL-only work. Otherwise a generated search can add jobs.
• Keep raw salary and experience labels. They are not normalized numeric ranges.
• Inspect description coverage before text analysis. Enabled descriptions can remain missing or short.
• Compare identifiers in your own destination. Runtime observation labels do not establish cross-run changes.

Limits and caveats

Only public Naukri India jobs are supported, without resumes, candidate profiles, private recruiter data, login-only fields or application submission. NaukriGulf is not supported despite the historical slug, and this tool is not affiliated with Naukri.

Sources can combine generated keyword/location searches and supplied URLs. Location alone generates a general search. Clear keyword and location prefills for URL-only collection. Use supported keyword/location paths rather than expecting arbitrary URL filters or browser sort order. Source/input order is retained without date or salary sorting. The hidden maxJobs alias overrides maxItems when supplied.

ExperienceMin, experienceMax and changedSince do not provide reliable experience selection or incremental collection. Posting time, salary and experience remain source text, workMode can be a code, and descriptions can be truncated or short excerpts. Missing optional fields remain null, skills can be empty and applyUrl can be the job URL rather than an external form.

No built-in change detection exists. FirstSeenAt, lastSeenAt and scrapedAt are observations within the current run, and changeType is always new. Keep your own job-ID or URL joins to compare datasets.

Postings can disappear, access can be blocked and deadlines can reduce coverage. The current implementation fails when no jobs are extracted, which alone does not prove no matching jobs, privacy or deletion. A successful run with some jobs does not establish that every input completed. RUN-SUMMARY on successful completion gives saved and queued-page counts and work skipped near the deadline, rather than a per-input coverage report or guaranteed record after failure.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~naukri-naukrigulf-jobs-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "site": "naukri",
  "keywords": [
    "software engineer"
  ],
  "location": "Bangalore",
  "maxItems": 5,
  "includeDescription": true
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/naukri-naukrigulf-jobs-scraper').call({
  "site": "naukri",
  "keywords": [
    "software engineer"
  ],
  "location": "Bangalore",
  "maxItems": 5,
  "includeDescription": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/naukri-naukrigulf-jobs-scraper').call(run_input={'site': 'naukri', 'keywords': ['software engineer'], 'location': 'Bangalore', 'maxItems': 5, 'includeDescription': True})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents

You can ask your AI assistant to collect data with Naukri Jobs Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Naukri Jobs Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/naukri-naukrigulf-jobs-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Naukri Jobs Scraper by Fetch Cat, or give it the identifier fetch_cat/naukri-naukrigulf-jobs-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s Naukri Jobs Scraper to collect up to 5 Naukri India software engineer jobs in Bangalore with descriptions enabled. Keep source links, employers and skills, marking short or missing descriptions without claiming complete job content.”
• “Collect up to 5 Naukri India data analyst jobs in Bangalore with descriptions off. Retain source salary and experience text for my analysis without converting it into guaranteed numeric eligibility or supporting NaukriGulf.”
• “Retrieve up to 5 Naukri India backend developer jobs in Bangalore with descriptions enabled. Keep job IDs or URLs and collection times for comparison with my own prior export, without treating the constant new label as change detection.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

Does this require a Naukri login?

No. It uses public job information. It is not affiliated with Naukri.

Can I use any Naukri search URL?

Use keyword/location path URLs. The Actor does not reproduce every browser search filter or sort order. For a URL-only run, clear both keywords and location as described above.

Why are there fewer results or empty fields?

The source may not expose all requested information, or access may be restricted. Check the run details and try a small, relevant keyword/location query. A successful run with some jobs does not prove every input completed.

Related Actors

• LinkedIn Jobs Scraper — public LinkedIn job research.
• Greenhouse Jobs Scraper — employer job boards on Greenhouse.
• Ashby Jobs Scraper — employer job boards on Ashby.
• SmartRecruiters Jobs Scraper — SmartRecruiters listings.
• Workday Jobs Scraper — Workday career listings.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥