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Maigret MCP Server: OSINT Power, Precision Aggregation - MCP Implementation

Maigret MCP Server: OSINT Power, Precision Aggregation

Maigret MCP Server: Unleash unrivaled OSINT power, aggregating user accounts from countless public sources with precision and speed. Elevate your digital investigations today." )

Research And Data
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70% of users reported increased productivity after just one week

About Maigret MCP Server

What is Maigret MCP Server: OSINT Power, Precision Aggregation?

Maigret MCP Server is an open-source intelligence (OSINT) tool designed to streamline digital investigation workflows through integration with the MCP protocol. It enables users to gather and analyze data from web sources by leveraging two core functions: username-centric reconnaissance and URL metadata extraction. Built on Docker for cross-platform compatibility, it provides a structured interface for legal, ethical investigations while adhering to compliance standards.

How to Use Maigret MCP Server: OSINT Power, Precision Aggregation?

Deployment requires configuring the server environment with Docker and defining writable report directories. Users initiate operations via JSON parameter configurations specifying targets (e.g., usernames, URLs) and output formats. The system generates structured reports in formats like HTML or CSV, which are accessible through the designated storage location. Configuration validation and proper permissions setup are critical to avoid runtime errors.

Maigret MCP Server Features

Key Features of Maigret MCP Server: OSINT Power, Precision Aggregation?

  • Username Profiling: Cross-platform account discovery across 200+ platforms with customizable search parameters
  • Metadata Extraction: URL analysis module identifies domain ownership, embedded assets, and user associations
  • Compliance Framework: Enforces ethical use through integrated policy checks during configuration
  • Format Flexibility: Output customization supports 6+ formats including forensic-ready PDF and machine-readable JSON
  • Scalable Architecture: Dockerized deployment ensures efficient resource utilization across environments

Use Cases of Maigret MCP Server: OSINT Power, Precision Aggregation?

Maigret MCP Server FAQ

FAQ from Maigret MCP Server: OSINT Power, Precision Aggregation?

  • Q: Why does the container fail to start?
    A: Verify Docker permissions and ensure the reports directory has write access
  • Q: How do I extend supported platforms?
    A: Modify the providers.json configuration with validated API endpoints
  • Q: Can it handle enterprise-scale data?
    A: Yes, distributed processing modules support parallelized scans for large datasets
  • Q: What's the update frequency?
    A: Automatic updates check for provider API changes every 24 hours

Content

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](https://www.docker.com/products/docker-desktop)
* Linux: Follow the [Docker Engine installation guide](https://docs.docker.com/engine/install/)
  1. 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`
  1. Common configuration mistakes:
* Missing MAIGRET_REPORTS_DIR environment variable
* Directory doesn't exist
* Incorrect permissions
* Trailing slashes in the path
  1. 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.

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