Naukri Job Scraper — India’s Largest Job Board

What does Naukri Scraper do?

Naukri Scraper extracts structured job data from naukri.com — including salary data, contact details, company metadata, full descriptions, and skill tags. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them, incremental monitoring that only returns new or changed results on recurring runs, and a compact output mode for AI-agent and MCP workflows.

What data can you extract from naukri.com?

Each result includes Core listing fields (jobId, title, experienceText, minimumExperience, maximumExperience, salary, salaryMin, and salaryMax, and more), detail fields when enrichment is enabled (description, descriptionHtml, descriptionMarkdown, roleCategory, jobRole, and vacancy), contact and apply information (applyCount), and company metadata (companyName, companyId, companyWebsite, and companyDescription). Descriptions are available in three formats: plain text, raw HTML, and Markdown (ideal for RAG pipelines and LLM consumption). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• keyword — Job search keyword (e.g. 'python developer', 'data analyst'). Not required if jobIds is provided.
• jobIds — Fetch specific jobs by their Naukri job IDs (skips keyword search).
• location — Filter by location (e.g. 'Bangalore', 'Mumbai', 'Delhi')
• maxResults — Maximum number of jobs to return (0 = unlimited) (default: 25)
• fetchDetails — Fetch full job details. Enables: description, roleCategory, functionalArea, jobRole, employmentType, educationUG, educationPG, applyCount, vacancy, workMode, companyDescription, companyWebsite. Slower — one extra request per job. (default: false)
• incremental — Only return new or changed jobs since last run (state scoped per keyword+location) (default: false)
• stateKey — Override the incremental state key. By default scoped to keyword+location. Use this to isolate state for different workflows using the same query.
• compact — Return only core fields (jobId, title, company, location, salary, experience, skills, createdDate, portalUrl, description). Ideal for AI agents and MCP workflows. (default: false)
• descriptionMaxLength — Truncate job descriptions to this many characters (0 or empty = no truncation)
• experienceMin — Minimum years of experience filter
• experienceMax — Maximum years of experience filter
• salary — Salary range filter in lakhs per annum
• skills — Filter by skill names (e.g. ["Python", "Django", "AWS"]). Appended to the search keyword for server-side matching.
• workMode — Filter by work arrangement: office, remote, hybrid, or temporary_wfh
• freshness — Only show jobs posted within this many days (1, 3, 7, 15, or 30)
• cityTypeGid — Filter by Naukri city ID (e.g. 97 for Bengaluru, 17 for Hyderabad)
• groupId — Filter to a single company group (e.g. 10476 for Accenture, 223346 for TCS)
• companyId — Filter to a specific company entity (e.g. 1354 for Virtusa). Different ID-space from groupId.
• companyGroupIds — Crawl multiple company groups in parallel by ID
• roleCategory — Post-filter by role category (e.g. 'Software Engineering'). Requires fetchDetails.
• industry — Post-filter by industry (e.g. 'IT Services'). Requires fetchDetails.
• sortBy — Sort by relevance or date

Input examples

Basic search — 50 Python developer jobs in Bangalore:

{
  "keyword": "python developer",
  "location": "Bangalore",
  "maxResults": 50
}

→ returns summary-level data (title, salary, skills, company, location)

Filtered search with details — remote React jobs, 0–3 years experience, sorted by date:

{
  "keyword": "react developer",
  "skills": ["React", "TypeScript", "Node.js"],
  "workMode": "remote",
  "experienceMin": 0,
  "experienceMax": 3,
  "sortBy": "date",
  "fetchDetails": true,
  "maxResults": 100
}

→ returns full descriptions, education requirements, apply counts, company profiles

Incremental monitoring — daily scheduled run that only returns new listings:

{
  "keyword": "data scientist",
  "location": "Mumbai",
  "incremental": true,
  "fetchDetails": true,
  "maxResults": 0
}

→ first run returns all matches; subsequent runs return only new/changed jobs

Company-specific crawl — all Accenture jobs in Bengaluru, compact output for AI agents:

{
  "groupId": 10476,
  "cityTypeGid": 97,
  "compact": true,
  "descriptionMaxLength": 500,
  "fetchDetails": true,
  "maxResults": 0
}

→ returns compact JSON with truncated descriptions, ideal for MCP/LLM pipelines

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
  "jobId": "100426916818",
  "title": "Custom Software Engineer",
  "companyName": "Accenture",
  "companyId": 27117,
  "experienceText": "0-1 Yrs",
  "minimumExperience": 0,
  "maximumExperience": 1,
  "salary": "Not disclosed",
  "salaryMin": null,
  "salaryMax": null,
  "salaryCurrency": null,
  "location": "Chennai",
  "skills": [
    "software engineer",
    "kubernetes",
    "rest",
    "restful",
    "load balancing",
    "api gateway",
    "hibernate",
    "redis"
  ],
  "createdDate": "2026-04-10T10:28:15.508Z",
  "portalUrl": "https://www.naukri.com/job-listings-custom-software-engineer-accenture-solutions-pvt-ltd-chennai-0-to-1-years-100426916818",
  "logoPath": "https://img.naukimg.com/logo_images/groups/v1/10476.gif",
  "industry": "IT Services & Consulting",
  "viewCount": 2366,
  "companyWebsite": null,
  "ambitionBox": {
    "url": "https://www.ambitionbox.com/reviews/accenture-reviews?utm_campaign=srp_ratings&utm_medium=desktop&utm_source=naukri",
    "rating": "3.7",
    "reviewsCount": 73082
  },
  "description": "Project Role : Custom Software Engineer Project Role Description : Analyze, design, code and test multiple components of application code across one or more clients...",
  "descriptionHtml": "<b>Project Role :</b>Custom Software Engineer<br /><b><br /><br />Project Role Description :</b>Analyze, design, code and test multiple components of application code across one or more clients...",
  "descriptionMarkdown": "**Project Role :**Custom Software Engineer\n**Project Role Description :**Analyze, design, code and test multiple components of application code across one or more clients...",
  "roleCategory": "Software Development",
  "functionalArea": "Engineering - Software & QA",
  "jobRole": "Search Engineer",
  "employmentType": "Full Time, Permanent",
  "educationUG": [
    "B.Tech / B.E. in Any Specialization"
  ],
  "educationPG": [
    "Any Postgraduate"
  ],
  "applyCount": 719,
  "vacancy": 0,
  "wfhType": "office",
  "companyDescription": "About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security...",
  "scrapedAt": "2026-04-12T21:33:55.000Z",
  "searchKeyword": "software engineer"
}

In compact mode, output is reduced to core fields: jobId, title, companyName, location, salary, experienceText, skills, createdDate, portalUrl, and description.

How to scrape naukri.com

1. Go to Naukri Jobs Feed in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set maxResults to control how many results you need.
4. Enable fetchDetails if you need full descriptions, contact info, or company data.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract job data from naukri.com for market research and competitive analysis.
• Track salary trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Build outreach lists using contact details and apply URLs from listings.
• Research company hiring patterns, employer profiles, and industry distribution.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.
• Analyze skill demand across listings using structured skill tags.

How much does it cost to scrape naukri.com?

Naukri Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.01 per run
• Per result: $0.002 per job record

Example costs:

• 10 results: $0.03
• 100 results: $0.21
• 500 results: $1.01

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 200 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.41	$0.03	$0.38 (93%)	$0.87
15% — moderate broad query	$0.41	$0.07	$0.34 (83%)	$2.03
30% — high-volume aggregator	$0.41	$0.13	$0.28 (68%)	$3.77

Full re-scrape monthly cost at daily polling: $12.30. First month with incremental costs $1.28 / $2.44 / $4.18 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same.

FAQ

How many results can I get from naukri.com?

The number of results depends on the search query and available listings on naukri.com. Use the maxResults parameter to control how many results are returned per run.

Does Naukri Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Naukri Scraper with other apps?

Yes. Naukri Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Naukri Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Naukri Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape naukri.com?

This actor extracts publicly available data from naukri.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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