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🚀 Linkedin Job Scraper - Ultra Fast and Detailed

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Developed by

John Patrick Vicente

🚀 Fast & Affordable LinkedIn Job Scraper with complete filters & enriched job data - qualifications, application deadline and more. Perfect for job hunters, recruiters and market analysis. Works well with n8n and MCPs

5.0 (1)

Pricing

$0.80 / 1,000 results

Last modified

19 hours ago

Automation

Jobs

Lead generation

You can access the 🚀 Linkedin Job Scraper - Ultra Fast and Detailed 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=patrickvicente/linkedin-job-scraper---ultra-fast-and-detailed",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with LinkedIn Job Data Extractor - Fast Recruitment Intelligence

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=patrickvicente/linkedin-job-scraper---ultra-fast-and-detailed 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=patrickvicente/linkedin-job-scraper---ultra-fast-and-detailed",
            "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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