Metis — Username OSINT Reconnaissance Engine

Metis is an autonomous, high-performance open-source intelligence (OSINT) tool designed to scan 700+ web platforms for usernames, extract rich profile metadata, and generate interactive HTML intelligence reports.

Metis operates in two modes:

1. Interactive CLI: Fast terminal scanning with live progress, colored indicators, result tables, and direct HTML/JSON report generation.
2. Web Service: Complete FastAPI web application providing real-time Server-Sent Events (SSE) streaming, interactive card layouts (Masonry & Grouped by category), avatar preview modals, and one-click HTML report export.

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Preview

Quick Start

Installation

git clone https://github.com/ayxkaddd/metis

cd metis

# Create virtual environment and activate
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

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Mode 1: Command Line Interface (CLI)

Basic Search

python main.py johndoe

Save Styled HTML Report

# Save an interactive standalone HTML report
python main.py johndoe -o johndoe_report.html

# Or explicitly using --html
python main.py johndoe --html report.html

Filter by Categories

Filter scans by specific platform categories (e.g. coding, social, tech, gaming, finance):

python main.py johndoe -c coding,social,tech -o dev_report.html

Include Search Engines & Tune Concurrency

python main.py johndoe --ddg -t 40 --timeout 15 -o full_scan.html

CLI Options

Argument	Description
username	Target username to investigate
-o, --output <file>	Save output (.html for HTML report, .json for raw JSON)
--html <file>	Explicitly save interactive, styled HTML report
--json <file>	Save raw results to a JSON file
-c, --category <list>	Comma-separated categories to scan (coding, social, tech, etc.)
--no-extract	Disable deep profile extraction (socid-extractor)
--ddg	Include DuckDuckGo search queries
-t, --concurrency <n>	Max concurrent HTTP connections (default: 30)
--timeout <sec>	Timeout per website in seconds (default: 10)
-v, --verbose	Enable verbose debug logging

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Mode 2: Web Service

Launch the standalone web service:

python main.py --web

Custom host and port:

python main.py --web --host 0.0.0.0 --port 8000

Open your browser at:

• Web UI: http://localhost:8000
• Interactive Swagger API Docs: http://localhost:8000/docs