# Monster Jobs Scraper | Search, Details, Emails (`abotapi/monster-com`) Actor

Extract monster.com job listings with full descriptions, salary, company, location, geo, application, classification, compliance, and public email fields. Supports search URLs and direct job URLs.

- **URL**: https://apify.com/abotapi/monster-com.md
- **Developed by:** [Abot API](https://apify.com/abotapi) (community)
- **Categories:** Jobs, Automation, Developer tools
- **Stats:** 3 total users, 2 monthly users, 96.4% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 job records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Monster Jobs Scraper

Extract structured Monster job listings for recruiting intelligence, labor-market research, job-board feeds, and hiring analytics. The actor supports structured search inputs plus direct Monster search and job URLs. It preserves the full upstream job object while adding flat fields that export cleanly to JSON, CSV, Excel, and API clients.

### Why This Scraper?

- Search by keyword and location
- Filter by radius, workplace, date, employment type, and company
- Sort by relevance or newest first
- Accept multiple Monster search and direct job URLs
- Return full HTML descriptions, salary, employer, geo, application, classification, branding, and compliance data
- Preserve the complete raw job object for future fields
- Produce explicit flat CSV columns, including job ID, title, company, location, salary, dates, URLs, and coordinates
- Extract public email addresses found in returned job content

### Data You Get

| Field | Example |
|---|---|
| `jobId` | `00000000-0000-0000-0000-000000000000` |
| `title` | `Sample Software Engineer` |
| `companyName` | `Sample Company` |
| `location` | `New York, NY, US` |
| `datePosted` | `2026-01-01T00:00:00.000Z` |
| `employmentTypesText` | `FULL_TIME` |
| `salaryMin` | `100000` |
| `salaryMax` | `140000` |
| `salaryCurrency` | `USD` |
| `remote` | `true` |
| `applyUrl` | `https://www.monster.com/` |
| `latitude` | `40.7000` |
| `longitude` | `-74.0000` |
| `descriptionHtml` | Full returned HTML |
| `contactEmail` | `jobs@example.com` |
| `raw` | Complete source object |

### How to Use

Search:

```json
{
  "mode": "search",
  "query": "software engineer",
  "location": "New York, NY",
  "maxItems": 20
}
```

Remote jobs posted recently:

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

URL mode:

```json
{
  "mode": "url",
  "startUrls": [
    "https://www.monster.com/jobs/search?q=developer&where=Boston%2C+MA&page=1"
  ],
  "maxItems": 20
}
```

### Input Parameters

| Parameter | Default | Description |
|---|---:|---|
| `mode` | `search` | Structured search or URL mode |
| `query` | `software engineer` | Search keyword |
| `location` | `New York, NY` | Search location |
| `radius` | `30` | Radius in miles |
| `workplace` | `all` | All workplaces or remote only |
| `datePosted` | `all` | Posting recency |
| `employmentType` | `all` | Employment type |
| `company` | empty | Employer name filter |
| `sortBy` | `relevance` | Relevance or newest first |
| `startUrls` | sample URL | Search and direct job URLs |
| `enrichEmails` | `true` | Extract public emails from returned content |
| `maxItems` | `20` | Maximum matching rows to save |
| `maxPages` | `2` | Default two-page run; set `0` for no page limit |
| `maxConcurrency` | `2` | Maximum parallel pages |
| `minConcurrency` | `1` | Minimum parallel pages |
| `maxRequestRetries` | `6` | Fresh-connection retries |
| `proxy` | Residential | Connection configuration |

`maxItems` is a maximum, not a guaranteed result count. A run can return fewer records when fewer current jobs match the selected source, keyword, location, and filters.

### Output Example

> Sample shape, values are illustrative placeholders, not from a live job.

```json
{
  "jobId": "00000000-0000-0000-0000-000000000000",
  "title": "Sample Software Engineer",
  "companyName": "Sample Company",
  "location": "New York, NY, US",
  "datePosted": "2026-01-01T00:00:00.000Z",
  "employmentTypes": ["FULL_TIME"],
  "employmentTypesText": "FULL_TIME",
  "salaryMin": 100000,
  "salaryMax": 140000,
  "salaryCurrency": "USD",
  "remote": true,
  "applyUrl": "https://www.monster.com/",
  "jobUrl": "https://www.monster.com/",
  "contactEmail": "jobs@example.com",
  "descriptionText": "Sample job description.",
  "raw": {},
  "scrapedAt": "2026-01-01T00:00:00.000Z"
}
```

### Plan Requirement

Apify Residential proxy is strongly recommended. Datacenter and free-tier connections can have lower reliability. The actor automatically retries incomplete pages with fresh sessions.

CSV exports use the dataset `overview` view with explicit flat fields. This prevents nested-only records from producing blank CSV files.

# Actor input Schema

## `mode` (type: `string`):

Choose structured search mode or URL mode.

## `query` (type: `string`):

Job title, skill, or keyword.

## `location` (type: `string`):

City, state, ZIP code, or country.

## `radius` (type: `integer`):

Search radius around the selected location.

## `workplace` (type: `string`):

Return all workplaces or remote jobs only.

## `datePosted` (type: `string`):

Limit results by posting recency.

## `employmentType` (type: `string`):

Limit results to one employment type.

## `company` (type: `string`):

Optional case-insensitive employer filter.

## `sortBy` (type: `string`):

Sort results by relevance or newest posting date.

## `startUrls` (type: `array`):

Monster search result URLs or direct job-opening URLs.

## `enrichEmails` (type: `boolean`):

Extract email addresses present in the returned job description and employer metadata.

## `maxItems` (type: `integer`):

Maximum matching rows to save. Fewer may be returned when fewer live jobs match.

## `maxPages` (type: `integer`):

Default is 2 pages for a quick representative run. Set 0 for no page limit; the run still stops at Max items or when results end.

## `proxy` (type: `object`):

Apify Residential is recommended. Datacenter and free-tier connections have lower reliability.

## Actor input object example

```json
{
  "mode": "search",
  "query": "software engineer",
  "location": "New York, NY",
  "radius": 30,
  "workplace": "all",
  "datePosted": "all",
  "employmentType": "all",
  "sortBy": "relevance",
  "startUrls": [
    "https://www.monster.com/jobs/search?q=software+engineer&where=New+York%2C+NY&page=1"
  ],
  "enrichEmails": true,
  "maxItems": 20,
  "maxPages": 2,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mode": "search",
    "startUrls": [
        "https://www.monster.com/jobs/search?q=software+engineer&where=New+York%2C+NY&page=1"
    ],
    "proxy": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("abotapi/monster-com").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "mode": "search",
    "startUrls": ["https://www.monster.com/jobs/search?q=software+engineer&where=New+York%2C+NY&page=1"],
    "proxy": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("abotapi/monster-com").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "mode": "search",
  "startUrls": [
    "https://www.monster.com/jobs/search?q=software+engineer&where=New+York%2C+NY&page=1"
  ],
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call abotapi/monster-com --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=abotapi/monster-com",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/fhymQM9ofQRZoy1eP/builds/8CyuNtgouy7a4hdON/openapi.json