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Linkedin Mutual Connections Parser

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Linkedin Mutual Connections Parser

Linkedin Mutual Connections Parser

saswave/linkedin-mutual-connections-parser
Try for free

3 days trial then $25.00/month - No credit card required now

Allows you to extract all informations from mutual connections of a linkedin profile url (1st and 2nd). Full name, jobtitle, premium status, followers, linkedin url, network distance, location, number of mutual connections. Does not need to be in your network to check for mutual connections

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Maintained by Community

Actor Metrics

  • 38 monthly users

  • 5.0 / 5 (1)

  • 9 bookmarks

  • 89% runs succeeded

  • 3.3 days response time

  • Created in Nov 2023

  • Modified 3 months ago

You can access the Linkedin Mutual Connections Parser 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=saswave/linkedin-mutual-connections-parser"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Linkedin Mutual Connections Parser via Model Context Protocol (MCP) server

MCP server lets you use Linkedin Mutual Connections Parser 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 Mutual Connections Parser 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      "url": "https://www.linkedin.com/in/thomas-l/",
8      "cookies": [
9            {
10                  "domain": ".linkedin.com",
11                  "expirationDate": 1742798742.32278,
12                  "hostOnly": false,
13                  "httpOnly": false,
14                  "name": "test",
15                  "path": "/",
16                  "sameSite": "no_restriction",
17                  "secure": true,
18                  "session": false,
19                  "storeId": "0",
20                  "value": "To be changed. Check readme on how to extract cookie session from browser",
21                  "id": 1
22            }
23      ]
24},
25    "name": "saswave/linkedin-mutual-connections-parser"
26  }
27}'

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 Mutual Connections Parser

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        "saswave/linkedin-mutual-connections-parser"
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.