
Linkedin Jobs Scraper - PPR
Pay $1.00 for 1,000 results

Linkedin Jobs Scraper - PPR
Pay $1.00 for 1,000 results
Scrape jobs from linkedin jobs search results along with company details. Get key information to find contact info
Actor Metrics
465 monthly users
5.0 / 5 (2)
79 bookmarks
>99% runs succeeded
21 hours response time
Created in Aug 2024
Modified 17 days ago
You can access the Linkedin Jobs Scraper - 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.
1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=curious_coder/linkedin-jobs-scraper"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa
Using Linkedin Jobs Scraper - PPR via Model Context Protocol (MCP) server
MCP server lets you use Linkedin Jobs Scraper - PPR 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 Linkedin Jobs Scraper - PPR 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": {
7 "urls": [
8 "https://www.linkedin.com/jobs/search/?position=1&pageNum=0"
9 ],
10 "count": 10
11},
12 "name": "curious_coder/linkedin-jobs-scraper"
13 }
14}'
The response should be: Accepted
. You should received response via SSE (JSON) as:
1event: message
2data: {
3 "result": {
4 "content": [
5 {
6 "type": "text",
7 "text": "ACTOR_RESPONSE"
8 }
9 ]
10 }
11}
Configure local MCP Server via standard input/output for Linkedin Jobs Scraper - PPR
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",
7 "@apify/actors-mcp-server",
8 "--actors",
9 "curious_coder/linkedin-jobs-scraper"
10 ],
11 "env": {
12 "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13 }
14 }
15 }
16}
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.