Pricing

$0.99 / 1,000 jobs

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LinkedIn Jobs Scraper – Incredibly Fast ⚡️(PPR)

Try for free

Developed by

Data Wizard

Designed for both personal and professional use, our ⚡️ Blazing fast LinkedIn job scraper scrapes 1,000 listings in under 2 minutes. Built-in datacenter proxy rotation. No setup. Pay-per-result (PPR) pricing model. Export to CSV, JSON, and more.

4.0 (1)

Pricing

$0.99 / 1,000 jobs

Total users

Monthly users

Runs succeeded

>99%

Last modified

22 days ago

Lead generation

Jobs

You can access the LinkedIn Jobs Scraper – Incredibly Fast ⚡️(PPR) 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=data_wizard/linkedin-job-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with LinkedIn Jobs Scraper – Blazing Fast (Pay-per-result (PPR))

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=data_wizard/linkedin-job-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=data_wizard/linkedin-job-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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