Monster Scraper: Job Listings, Salaries and Employer Details

Monster Scraper turns Monster job search into structured data. Run a keyword and location search with filters for recency, employment type and remote work, or paste Monster search and direct job-opening links and let the actor page through them. Each record carries title, employer, salary, location and geo, dates, employment type, application links, the full HTML and plain-text description, optional public emails found in the listing, and the complete source object. Export to JSON, CSV or Excel, or pull results straight into your app through the API.

Why This Scraper?

• Two ways in. Run a structured keyword and location search, or paste Monster search and direct job-opening links; the same recency, employment type, company and sort filters narrow a pasted search link just like a structured search.
• Server-side filters. On searches, recency, employment type and remote-only are applied by Monster itself, so filtered-out jobs are never fetched or charged.
• Full description, twice over. The complete HTML description and a stripped plain-text version are both included, so you don't have to parse HTML yourself.
• Compensation, flattened, with optional emails. Salary range, currency, employment type, industry and Monster's own normalized title and skill enrichment come out as plain top-level fields, plus public emails from the listing when enabled.
• Nothing thrown away. The complete source job object rides along in raw, so a field this actor doesn't flatten today is still in the record.
• Incremental mode. Schedule the same search and receive only NEW, UPDATED and REAPPEARED jobs, with EXPIRED rows for jobs that disappeared.
• Cost stays predictable. Max items and Max pages cap how far a run goes before it grows unexpectedly.

Use Cases

• Recruiters and staffing agencies: track which employers are actively hiring, and for which roles and salary bands.
• Job board and aggregator sites: mirror Monster listings into your own search product with structured, exportable fields.
• Labor market researchers: sample salary, employment-type and location data across cities and industries.
• Sales and business development teams: build outreach lists from companies posting new roles.
• Compliance and market-rate teams: monitor posted salary ranges by employment type and region.

Data You Get

Sample shape: values are illustrative placeholders, not from a live record.

Field	Example
jobId	"11111111-2222-3333-4444-555555555555"
seoJobId	"senior-backend-engineer-austin-tx--11111111-2222-3333-4444-555555555555"
title	"Senior Backend Engineer"
companyName	"Cascade Analytics Inc."
companyLogo	https://media.example.com/logo.png
location	"Austin, TX, US"
latitude / longitude	30.2672 / -97.7431
datePosted	"2026-01-01T00:00:00.000Z"
dateRecency	"3 days ago"
validThrough	"2026-03-01T00:00:00.000Z"
status	"ACTIVE"
employmentTypesText	"FULL_TIME"
salaryMin / salaryMax	95000 / 130000
salaryCurrency	"USD"
remote	true
applyUrl	https://www.monster.com/job-openings/sample-role
jobUrl	https://www.monster.com/job-openings/sample-role--11111111-2222-3333-4444-555555555555
descriptionText	"Sample job description text."
contactEmail	"jobs@example.com"
skills	Object with extractions and scoredExtractions (each entry has a name such as KBSkills and a list of {id, value, score} skills), or empty when Monster's own enrichment provides none
raw	the complete source job object

When no live job matches, the dataset instead gets one diagnostic row (error: true, code: "ZERO_RESULTS") rather than nothing at all. When every connection attempt to Monster is refused, the run fails with the message "Could not load any results page (the requests failed), so nothing was collected. This is a connection problem, not an empty search. Please try again later."

How to Use

1. Pick a mode: search (structured keyword and location filters) or url (paste Monster search or job-opening links).
2. In search mode, fill in Keywords and Location. In url mode, paste one or more Monster links. The shared filters (recency, employment type, company, sort) narrow every search, whether structured or pasted as a link; a direct job-opening link is narrowed by Company only. With the Start URLs field left unedited, url mode scrapes one example of each supported shape (search with page, filtered search, SEO keyword and keyword+location pages, and a direct job-opening link). Search URLs honour page (start page) and rad (radius in miles); where=remote selects remote jobs. A pasted link without a location (for example a keyword-only page) searches the whole United States; Location and Workplace apply to search mode only. Keywords and Radius also come only from the link (a link without rad uses 30 miles, and a link without q has no keyword filter).
3. Set Max items and Max pages to control how far each source pages and how many rows you pay for.
4. Start the run, then download the dataset as JSON, CSV or Excel, or read it through the API.

Basic keyword search:

{
  "mode": "search",
  "query": "product manager",
  "location": "Chicago, IL",
  "maxItems": 20
}

Remote jobs, posted this week, newest first:

{
  "mode": "search",
  "query": "data engineer",
  "location": "United States",
  "workplace": "remote",
  "datePosted": "week",
  "sortBy": "date",
  "maxItems": 50
}

Paste a Monster search link:

{
  "mode": "url",
  "startUrls": [
    "https://www.monster.com/jobs/search?q=nurse&where=Dallas%2C+TX"
  ],
  "maxPages": 3,
  "maxItems": 60
}

Paste a direct job-opening link, filtered to one employer:

{
  "mode": "url",
  "startUrls": [
    "https://www.monster.com/job-openings/sample-role--11111111-2222-3333-4444-555555555555"
  ],
  "company": "cascade"
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/monster-com").call(run_input={"mode": "search", "query": "data engineer", "location": "Austin, TX"})
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], job["companyName"], job["salaryMin"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/monster-com').call({ mode: 'search', query: 'data engineer', location: 'Austin, TX' });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

How Max items and Max pages interact

Max items is a ceiling shared across every search and URL in one run, not a per-source guarantee: once it's reached, no further source is started. Max pages (default 2) limits how many pages each individual source walks before moving on; set it to 0 to let a source page until Max items is reached or the site runs out of results. Within one run, each source stops as soon as one of its own pages returns no job the run hasn't already collected, so raising Max pages only helps if there are genuinely more unseen jobs left to find.

Known limitation when pasted search links overlap. The "no new job on this page" check compares against every job collected so far in the whole run, not just the current link's own jobs. So if a later link's page is made up entirely of jobs an earlier link already returned, that later link stops right there, even on its very first page, and its deeper pages are never requested. A page with even one job the run hasn't seen yet does not trigger this. Example, with Max items set high enough to reach both links: link A (nurse jobs in Dallas) returns jobs 1 to 20. Link B (registered nurse jobs in Dallas) would serve jobs 1 to 20 again on page 1 and jobs 21 to 40 on page 2. Page 1 of link B holds only jobs link A already returned, so link B stops on page 1 and jobs 21 to 40 are never collected, even with Max pages set to 0. Raising Max pages does not help, because the stop happens before any page limit is reached. Workaround: when your links are likely to share results (the same keyword in nearby places, or similar keywords in one place), run each link as its own run, for example one saved task per link, for complete results.

Send results into your apps (MCP connectors)

Optionally pipe a condensed summary of each saved job into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape: the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each job (title plus key fields as plain text), not the full JSON. The complete record always stays in the Apify dataset. Incremental rows that are unchanged (even when Also return unchanged jobs is on) or suppressed are not sent.

1. Authorize a connector once under Apify > Settings > Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. If the picker is empty, you have not authorized a connector yet.
3. For Notion, also set the Notion parent page field to the page where items should be created.

The connection goes through Apify's MCP proxy, so this actor never sees your third-party credentials. The maxNotifyListings field caps how many items are sent to each connector per run. Leave mcpConnectors empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search (structured filters) or url (paste Monster links).
query	string	software engineer	Job title, skill, or keyword (search mode).
location	string	New York, NY	City, state, ZIP code, or country (search mode).
radius	integer	30	Search radius in miles around Location, 1 to 100 (search mode).
workplace	string	all	all workplaces or remote jobs only.
startUrls	array	sample URL	Monster search result URLs or direct job-opening URLs (url mode).
datePosted	string	all	Limit results by posting recency. Applies to structured searches and pasted search links (a link's own recency setting wins), not to direct job-opening links.
employmentType	string	all	Limit results to one employment type. Applies to structured searches and pasted search links, not to direct job-opening links.
company	string	empty	Case-insensitive employer name filter. Applies in both modes, including a single pasted job link.
sortBy	string	relevance	Sort by relevance or newest posting date. Applies to structured searches and pasted search links (a link's own sort setting wins).
enrichEmails	boolean	true	Extract public email addresses from the returned job content.
maxItems	integer	20	Maximum matching rows to save, shared across every source in the run.
maxPages	integer	0	Pages walked per source before moving on; 0 means no page limit (the run still stops at Max items, when results end, or when a page repeats).
scrapeAllPages	boolean	false	Ignore Max pages and walk every result page, still bounded by Max items.
startPage	integer	1	First result page for structured searches (pasted search links carry their own page).
pageSize	integer	20	Jobs requested per page, 1 to 50.
address	string	empty	Alias of location; wins when both are set.
postedWithinDays	string	any	any, 1, 3, 7, 14 or 30 days; overrides datePosted when not any. Three days uses the last-week window trimmed to three days.
country	string	US	Monster serves the United States only.
proxy	object	Apify Residential	Connection settings; the actor also manages its own connection.
incrementalMode	boolean	false	Return only NEW, UPDATED and REAPPEARED jobs since the last run of the same search.
stateKey	string	empty	Optional name of the remembered baseline.
emitUnchanged	boolean	false	Incremental mode: also write UNCHANGED jobs (never charged).
emitExpired	boolean	true	Incremental mode: write EXPIRED rows for jobs no longer listed after a complete walk (never charged).
resumeFromRunId	string	empty	Skip jobs an earlier run already saved.
mcpConnectors	array	empty	Optionally send results into your apps via Model Context Protocol connectors.
notionParentPageUrl	string	none	Notion page under which exported items are created (Notion connector only).
maxNotifyListings	integer	50	Maximum items sent to each connector per run; the dataset is unaffected.
ignoreFieldsForChanges	array	empty	Incremental mode: extra fields that must not trigger UPDATED.

Output Example

Sample shape: values are illustrative placeholders, not from a live record.

{
  "jobId": "11111111-2222-3333-4444-555555555555",
  "seoJobId": "senior-backend-engineer-austin-tx--11111111-2222-3333-4444-555555555555",
  "title": "Senior Backend Engineer",
  "companyName": "Cascade Analytics Inc.",
  "location": "Austin, TX, US",
  "latitude": 30.2672,
  "longitude": -97.7431,
  "datePosted": "2026-01-01T00:00:00.000Z",
  "dateRecency": "3 days ago",
  "status": "ACTIVE",
  "employmentTypes": ["FULL_TIME"],
  "employmentTypesText": "FULL_TIME",
  "salaryMin": 95000,
  "salaryMax": 130000,
  "salaryCurrency": "USD",
  "remote": true,
  "applyUrl": "https://www.monster.com/job-openings/sample-role",
  "jobUrl": "https://www.monster.com/job-openings/sample-role--11111111-2222-3333-4444-555555555555",
  "descriptionText": "Sample job description text.",
  "contactEmail": "jobs@example.com",
  "raw": {},
  "scrapedAt": "2026-01-01T00:00:00.000Z"
}

Dataset views

The dataset ships with four tabs in the Console: Jobs (overview), Salaries (salary range, currency, unit and normalized salary), Employers & contacts (company, logo, contact emails, apply link) and Locations (city, region, postal code, country, coordinates). All views read the same records; the fields are typed and nullable, and raw still carries the complete source object.

Plan Requirement

Monster sits behind a bot-protection interstitial. In our measurements plain datacenter connections were refused with an HTTP 403 on every search, filter, pagination, job-opening and home URL, so a datacenter proxy alone is not enough. The actor serves requests through its own managed connection and refreshes it when a request is refused, so the proxy group you pick under Connection is your own choice and cost and does not change which connection reads Monster. If every attempt is refused the run fails with a clear message, so retry later rather than raising Max items.

FAQ

How much does it cost?

Billing uses two events: apify-actor-start is charged once per run, and job-result is charged once per saved job record. The diagnostic ZERO_RESULTS row, and in incremental mode UNCHANGED and EXPIRED rows, are never charged. The Pricing tab shows current rates. Use Max items to cap the cost of any run.

Is it legal to scrape Monster?

This actor collects only publicly available job listings. You are responsible for how you use the data: follow Monster's terms and the laws that apply to you, and get legal advice before any commercial redistribution. Employer content such as logos and company descriptions may carry their own rights.

Can I schedule it to catch new postings?

Yes. Schedule the actor from the Schedules tab and switch on Only report changes since the last run. The actor remembers the jobs of the same search and writes only NEW, UPDATED and REAPPEARED jobs, each with changeType, changedFields, firstSeenAt and lastSeenAt. Unchanged jobs are skipped and not charged; with Also return unchanged jobs they are written as UNCHANGED, still not charged. Each row also carries the full apply, jobPosting and brandingExt blocks plus flattened companyBannerUrl and companyPhotos. Relative age labels (dateRecency, formattedDate), scrapedAt and raw never count as a change, while datePosted and validThrough do; add more with Ignore fields when detecting changes. With Report jobs that are no longer listed, baseline jobs missing from a run that walked the whole search are written as EXPIRED (not charged). A run capped by Max items or Max pages, or using direct job links, cannot prove a complete walk and reports no EXPIRED jobs. The baseline is keyed by your search settings, or by State name if set.

Why did my run return fewer jobs than Max items?

Max items is a ceiling shared across every search and URL in the run, not a per-source guarantee. A source stops early once its current page returns no job it hasn't already collected this run, once Max pages is reached, or once the site has no more results, whichever comes first. With several pasted links in one run, that first rule counts jobs collected by any earlier link, so a link whose first page repeats another link's jobs can stop before reaching its own new jobs; run overlapping links as separate runs for complete results (see Known limitation when pasted search links overlap above). Fewer live jobs can also simply mean fewer matches exist for your keywords, location, and filters.

Why does a single pasted job link sometimes return no job?

A direct job-opening link is filtered by Company only; Date posted, Employment type and Sort apply to searches and do not remove a directly linked job. If Company is set and that job's employer name doesn't contain the text you entered, the job is skipped, and the run saves only the ZERO_RESULTS diagnostic row described below.

Why did my run finish with one row, or fail?

If the connection works but nothing matches, the actor saves one diagnostic row (code: "ZERO_RESULTS") suggesting broader keywords, a wider location, fewer filters or a different Proxy configuration. If every connection attempt to Monster is refused and nothing was saved, the run fails with "Could not load any results page (the requests failed), so nothing was collected. This is a connection problem, not an empty search. Please try again later." A run also fails outright when none of the pasted links are usable Monster search or job URLs.

Can I use it with AI agents or MCP?

Yes. Call it through the Apify API or SDKs like any other actor, and wire its dataset into an agent or automation platform through Apify's integrations.

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