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Linkedin Email Extractor

clothefobia/linkedin-email-extractor

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1 day trial then $10.00/month - No credit card required now

Linkedin Email Extractor-Scrap Emails from Linkedin social media using unique technology with specific keyword

Developer

clothe fobia

Actor Metrics

78 Monthly users
5.0 / 5 (1)
20 bookmarks
>99% runs succeeded
Created in Jul 2024
Modified 2 days ago

Categories

You can access the Linkedin Email Extractor 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=clothefobia/linkedin-email-extractor"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Linkedin Email Extractor via Model Context Protocol (MCP) server

MCP server lets you use Linkedin Email Extractor 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 Email Extractor 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      "Keyword": "testkeyword",
8      "proxySettings": {
9            "useApifyProxy": false
10      }
11},
12    "name": "clothefobia/linkedin-email-extractor"
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 Email Extractor

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        "clothefobia/linkedin-email-extractor"
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.

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