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AI LinkedIn Job Matcher

Pricing

$5.00 / 1,000 jobs

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AI LinkedIn Job Matcher

AI LinkedIn Job Matcher

Developed by

James

Maintained by Community

AI LinkedIn Job Matcher helps job seekers find the most relevant LinkedIn job postings using NLP, and OpenAI's GPT-4. It analyzes job descriptions, matches them to resumes, and ranks opportunities by relevance. Automate job searching, save time and discover the best career matches easily!

0.0 (0)

Pricing

$5.00 / 1,000 jobs

0

Monthly users

16

Runs succeeded

>99%

Last modified

a month ago

You can access the AI LinkedIn Job Matcher 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=james.logantech/ai-linkedin-job-matcher"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using AI LinkedIn Job Matcher via Model Context Protocol (MCP) server

MCP server lets you use AI LinkedIn Job Matcher 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 AI LinkedIn Job Matcher 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      "query": "Software Engineer",
8      "location": "Australia",
9      "resume": "John Doe - Software Engineer with 5+ years of experience in Python, JavaScript, and cloud technologies. Skilled in React, Node.js, AWS, and Docker. Passionate about building scalable applications and optimizing performance.",
10      "max_results": 100
11},
12    "name": "james.logantech/ai-linkedin-job-matcher"
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 AI LinkedIn Job Matcher

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        "james.logantech/ai-linkedin-job-matcher"
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.

Pricing

Pricing model

Pay per result 

This Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.

Price per 1,000 items

$5.00