LinkedIn Jobs Scraper - Customized Filters with Notifications avatar
LinkedIn Jobs Scraper - Customized Filters with Notifications

Pricing

$30.00/month + usage

Go to Store
LinkedIn Jobs Scraper - Customized Filters with Notifications

LinkedIn Jobs Scraper - Customized Filters with Notifications

Developed by

Mohamed Moo

Mohamed Moo

Maintained by Community

Designed to help job seekers and HR professionals track job vacancies posted on LinkedIn in real-time. With Apify's power and flexibility, you can run the actor, specify search parameters like job title, location, and keywords, and receive instant notifications through Telegram.

0.0 (0)

Pricing

$30.00/month + usage

0

Total users

10

Monthly users

10

Runs succeeded

>99%

Last modified

a month ago

You can access the LinkedIn Jobs Scraper - Customized Filters with Notifications 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.

{
"mcpServers": {
"local-actors-mcp-server": {
"command": "npx",
"args": [
"-y",
"@apify/actors-mcp-server",
"--actors",
"mabdulmoghni/linkedin-jobs-scraper---customized-filters-with-notifications"
],
"env": {
"APIFY_TOKEN": "<YOUR_API_TOKEN>"
}
}
}
}

Configure MCP server with LinkedIn Jobs Scraper - Customized Filters with Notifications

You can interact with the MCP server via standard input/output - stdio (as shown above), which is ideal for local integrations and command-line tools such as the Claude desktop client, or you can interact with the server through Server-Sent Events (SSE) to send messages and receive responses, which looks as follows:

{
"mcpServers": {
"remote-actors-mcp-server": {
"type": "sse",
"url": "https://mcp.apify.com/sse?actors=mabdulmoghni/linkedin-jobs-scraper---customized-filters-with-notifications",
"headers": {
"Authorization": "Bearer <YOUR_API_TOKEN>"
}
}
}
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other supported 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.