mcp-maigret

MCP.Pizza Chef: BurtTheCoder

The mcp-maigret server is a Model Context Protocol (MCP) server that integrates the powerful OSINT tool Maigret into MCP-compatible applications. Maigret specializes in collecting user account information from a wide range of public sources, enabling comprehensive username searches across social networks and detailed URL analysis. This server facilitates seamless interaction with Maigret’s capabilities within environments like Claude Desktop, enhancing real-time OSINT workflows. Designed for ethical and legitimate use, mcp-maigret supports privacy-conscious research by respecting data protection laws and platform terms of service, making it a valuable tool for security researchers, investigators, and analysts.

Use This MCP server To

Search usernames across multiple social networks Analyze URLs for user account information Integrate OSINT data into AI workflows Automate public data collection for investigations Enhance security research with real-time OSINT Support ethical user data discovery Combine Maigret data with LLM analysis

README

Maigret MCP Server

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A Model Context Protocol (MCP) server for maigret, a powerful OSINT tool that collects user account information from various public sources. This server provides tools for searching usernames across social networks and analyzing URLs. It is designed to integrate seamlessly with MCP-compatible applications like Claude Desktop.

mcp-maigret MCP server

⚠️ Warning

This tool is designed for legitimate OSINT research purposes. Please:

  • Only search for information that is publicly available
  • Respect privacy and data protection laws
  • Follow the terms of service of the platforms being searched
  • Use responsibly and ethically
  • Be aware that some sites may rate-limit or block automated searches

Requirements

  • Node.js (v18 or later)
  • Docker
  • macOS, Linux, or Windows with Docker Desktop installed
  • Write access to the reports directory

Quick Start

Installing via Smithery

To install Maigret for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-maigret --client claude

Installing Manually

  1. Install Docker:

    • macOS: Install Docker Desktop
    • Linux: Follow the Docker Engine installation guide
  2. Install the server globally via npm:

npm install -g mcp-maigret
  1. Create a reports directory:
mkdir -p /path/to/reports/directory
  1. Add to your Claude Desktop configuration file:
{
  "mcpServers": {
    "maigret": {
      "command": "mcp-maigret",
      "env": {
        "MAIGRET_REPORTS_DIR": "/path/to/reports/directory"
      }
    }
  }
}

Configuration file location:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  1. Restart Claude Desktop

Alternative Setup (From Source)

If you prefer to run from source or need to modify the code:

  1. Clone and build:
git clone <repository_url>
cd mcp-maigret
npm install
npm run build
  1. Add to your Claude Desktop configuration:
{
  "mcpServers": {
    "maigret": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-maigret/build/index.js"],
      "env": {
        "MAIGRET_REPORTS_DIR": "/path/to/reports/directory"
      }
    }
  }
}

Features

  • Username Search: Search for a username across hundreds of social networks and websites
  • URL Analysis: Parse URLs to extract information and search for associated usernames
  • Multiple Output Formats: Support for txt, html, pdf, json, csv, and xmind formats
  • Site Filtering: Filter searches by site tags (e.g., photo, dating, us)
  • Docker-based: Reliable and consistent execution across environments

Tools

1. Username Search Tool

  • Name: search_username
  • Description: Search for a username across social networks and sites
  • Parameters:
    • username (required): Username to search for
    • format (optional, default: "pdf"): Output format (txt, html, pdf, json, csv, xmind)
    • use_all_sites (optional, default: false): Use all available sites instead of top 500
    • tags (optional): Array of tags to filter sites (e.g., ["photo", "dating"])

Example:

{
  "username": "test_user123",
  "format": "html",
  "use_all_sites": false,
  "tags": ["photo"]
}

2. URL Analysis Tool

  • Name: parse_url
  • Description: Parse a URL to extract information and search for associated usernames
  • Parameters:
    • url (required): URL to analyze
    • format (optional, default: "pdf"): Output format (txt, html, pdf, json, csv, xmind)

Example:

{
  "url": "https://example.com/profile",
  "format": "txt"
}

Troubleshooting

Docker Issues

  1. Verify Docker is installed and running:
docker --version
docker ps
  1. Check Docker permissions:
    • Ensure your user has permissions to run Docker commands
    • On Linux, add your user to the docker group: sudo usermod -aG docker $USER

Reports Directory Issues

  1. Verify the reports directory:

    • The directory specified in MAIGRET_REPORTS_DIR must exist
    • Your user must have write permissions to this directory
    • Check permissions: ls -la /path/to/reports/directory
  2. Common configuration mistakes:

    • Missing MAIGRET_REPORTS_DIR environment variable
    • Directory doesn't exist
    • Incorrect permissions
    • Trailing slashes in the path
  3. After fixing any issues:

    • Save the configuration file
    • Restart Claude Desktop

Error Messages

  • "Docker is not installed or not running": Install Docker and start the Docker daemon
  • "MAIGRET_REPORTS_DIR environment variable must be set": Add the environment variable to your configuration
  • "Error creating reports directory": Check directory permissions and path
  • "Error executing maigret": Check Docker logs and ensure the container has proper permissions

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

mcp-maigret FAQ

How do I install the mcp-maigret server?
You can install mcp-maigret by following the instructions on its GitHub repository, which typically involves cloning the repo and running the server with required dependencies.
Can mcp-maigret be used with different MCP hosts?
Yes, mcp-maigret is designed to integrate with any MCP-compatible host, such as Claude Desktop, enabling flexible OSINT workflows.
What kind of data sources does mcp-maigret search?
It collects publicly available user account information from various social networks and public websites, respecting privacy and legal guidelines.
Is mcp-maigret suitable for automated OSINT tasks?
Yes, it supports automation of username searches and URL analysis within AI-enhanced workflows.
How does mcp-maigret ensure ethical use?
The server is intended for legitimate OSINT research only, encouraging users to respect privacy laws, platform terms, and use data responsibly.
Does mcp-maigret handle rate limiting from target sites?
While mcp-maigret can encounter rate limits, users should be aware and manage requests responsibly to avoid service disruptions.
Can mcp-maigret be combined with LLMs like OpenAI, Claude, or Gemini?
Yes, it integrates smoothly with LLMs such as OpenAI, Anthropic Claude, and Google Gemini for enhanced data analysis.
What programming languages or environments does mcp-maigret support?
It primarily runs as a server compatible with MCP clients, typically requiring Python and standard MCP tooling.