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Careerone Job Scraper

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Careerone Job Scraper

Careerone Job Scraper

websift/careerone-job-scraper
Try for free

2 hours trial then $10.00/month - No credit card required now

Scrape job listings from Careerone.com.au with ease! This actor extracts detailed job information based on customizable search parameters, returning results in structured JSON format. Perfect for lead generation, market research, or job seekers.

You can access the Careerone Job Scraper programmatically from your own applications by using the Apify API. You can choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1# Start Server-Sent Events (SSE) session
2curl https://actors-mcp-server.apify.actor/sse?token=<APIFY_TOKEN>
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Careerone Job Scraper via Model Context Protocol (MCP) server

MCP server lets you use Careerone Job Scraper within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Careerone Job Scraper Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {  # Actor inputs
7        "searchTerm": ...,
8        ...
9    },
10    "name": "uJXCDECdUHafli2PI"
11  }
12}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [{
5      "type": "text"
6      "text": "ACTOR_RESPONSE"
7    }]
8  }
9}

Configure local MCP Server via standard input/output for Careerone Job Scraper

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2"mcpServers": {
3  "actors-mcp-server": {
4    "command": "npx",
5    "args": [
6      "-y", "@apify/actors-mcp-server",
7      "--actors", "uJXCDECdUHafli2PI"
8    ],
9    "env": {
10       "APIFY_TOKEN": "YOUR_API_TOKEN"
11    }
12  }
13}
14}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.

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  • Created in Feb 2025

  • Modified 9 hours ago