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$6.00 / 1,000 jobs

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LinkedIn Job Details Scraper

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Developed by

Piotr Vassev

The LinkedIn Job Details Scraper extracts job data from LinkedIn job detail URLs, capturing job titles, company names, logos, locations, posting times, descriptions, number of applicants, job criteria, similar jobs, and related job listings—ideal for recruitment insights and job market analysis.

0.0 (0)

Pricing

$6.00 / 1,000 jobs

Total users

Monthly users

Runs succeeded

>99%

Issues response

18 days

Last modified

4 months ago

Jobs

Lead generation

Automation

You can access the LinkedIn Job Details Scraper programmatically from your own applications by using the Apify API. You can also 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.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=piotrv1001/linkedin-job-details-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with LinkedIn Job Details Scraper

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=piotrv1001/linkedin-job-details-scraper along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=piotrv1001/linkedin-job-details-scraper",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

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