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linkedin-osint-mcp

linkedin-osint-mcp

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github.com/djackreuterSocial Media2Updated 61w ago
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About linkedin-osint-mcp

linkedin-osint-mcp is an MCP server that uses Serper-backed Google searches to collect employee usernames from LinkedIn. It is intended for OSINT tasks such as finding people associated with an organization and formatting the results.

Key features

  1. 01Search Google via Serper
  2. 02Collect LinkedIn employee usernames
  3. 03Search across multiple result pages
  4. 04Format names as email addresses
  5. 05Save results to CSV

Use cases

  1. 01Find LinkedIn profiles associated with an organization
  2. 02Expand employee searches across result pages
  3. 03Format names into an email pattern
  4. 04Export collected names to CSV

MCP support

It exposes LinkedIn employee-search functionality to MCP clients. Configure it in an MCP client and provide a Serper API key.

#linkedin-osint#data-gathering#osint-tool

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

linkedin-osint-mcp

Uses Serper to perform a Google search to gather a list of employees from LinkedIn.

Usage

  • Install uv
  • Get an API key from Serper and add it to .env file.
  • Configure MCP client:
    E.g., Claude Desktop
{
    "mcpServers": {
        "linkedin_osint": {
            "command": "uv",
            "args": [
                "--directory",
                "C:\\path\\\\to\\linkedin-osint-mcp",
                "run",
                "main.py"
            ]
        }
    }
}

Example Queries

"Get a list of users that work at Bullworth Academy." // basic
"Get a list of users that work at Bullworth Academy and find as many as you can." // will search through multiple pages
"Find all users that work at Bullworth Academy and format the results as "[email protected]" and save to a csv file." // format names into emails

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