Tracehunt

by Hayatelin

245 downloads
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GitHub

About

TraceHunt is an MCP server (and CLI) for OSINT username reconnaissance across 480+ platforms. Tools: hunt_username() returns where a handle exists, and footprint_score() returns a 0-100 digital-footprint score. Python, MIT, runs locally, no API keys, privacy-first.

Details

Author
Hayatelin
Downloads
245
Categories
Developer Tools, Security

- Username reconnaissance across 480+ platforms.
- hunt_username() finds where a handle exists.
- footprint_score() returns digital-footprint score 0–100.
- Written in Python, MIT licensed.
- Runs locally, no API keys required.
- Privacy-first: data stays on your machine.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Tracehunt
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Run the MCP server and invoke the hunt_username() and footprint_score() tools through any MCP client, or use the CLI directly. No installation steps or configuration keys are provided in the README.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "tracehunt": {
            "tracehunt": {
                "command": "python",
                "args": [
                    "mcp/tracehunt_mcp.py"
                ]
            }
        }
    }
}

McpServers

{
    "tracehunt": {
        "command": "python",
        "args": [
            "mcp/tracehunt_mcp.py"
        ]
    }
}

TraceHunt is an MCP server (and CLI) for OSINT username reconnaissance across 480+ platforms. Tools: hunt_username() returns where a handle exists, and footprint_score() returns a 0-100 digital-footprint score. Python, MIT, runs locally, no API keys, privacy-first.

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