About ExternalAttacker MCP Server
ExternalAttacker MCP Server is a modular external attack surface mapping tool that exposes several ProjectDiscovery and fuzzing utilities through a natural language interface. It targets security researchers and bug bounty hunters who need automated reconnaissance across domains, hosts and services.
Key features
- 01Subdomain discovery with subfinder
- 02Port scanning with naabu
- 03HTTP service analysis with httpx
- 04CDN detection with cdncheck
- 05TLS configuration analysis with tlsx
- 06Directory fuzzing with ffuf and gobuster
- 07DNS enumeration with dnsx
Use cases
- 01Enumerating subdomains of a domain from a plain English query
- 02Checking open ports on a given IP address
- 03Analyzing the SSL configuration of a website
MCP support
This project is an MCP server that exposes these scanning tools to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEExternalAttacker MCP Server

Model Context Protocol (MCP) Server for External Attack Surface Management
ExternalAttacker is a powerful integration that brings automated scanning capabilities with natural language interface for comprehensive external attack surface management and reconnaissance.
🔍 Automated Attack Surface Management with AI!
Scan domains, analyze infrastructure, and discover vulnerabilities using natural language.
🔍 What is ExternalAttacker?
ExternalAttacker combines the power of:
- Automated Scanning: Comprehensive toolset for external reconnaissance
- Model Context Protocol (MCP): An open protocol for creating custom AI tools
- Natural Language Processing: Convert plain English queries into scanning commands
📱 Community
Join our Telegram channel for updates, tips, and discussion:
- Telegram: https://t.me/root_sec
✨ Features
- Natural Language Interface: Run scans using plain English
- Comprehensive Scanning Categories:
- 🌐 Subdomain Discovery (subfinder)
- 🔢 Port Scanning (naabu)
- 🌍 HTTP Analysis (httpx)
- 🛡️ CDN Detection (cdncheck)
- 🔐 TLS Analysis (tlsx)
- 📁 Directory Fuzzing (ffuf, gobuster)
- 📝 DNS Enumeration (dnsx)
📋 Prerequisites
- Python 3.8 or higher
- Go (for installing tools)
- MCP Client
🔧 Installation
-
Clone this repository:
git clone https://github.com/mordavid/ExternalAttacker-MCP.git cd ExternalAttacker -
Install Python dependencies:
pip install -r requirements.txt -
Install required Go tools:
go install -v github.com/projectdiscovery/subfinder/v2/cmd/subfinder@latest go install -v github.com/projectdiscovery/naabu/v2/cmd/naabu@latest go install -v github.com/projectdiscovery/httpx/cmd/httpx@latest go install -v github.com/projectdiscovery/cdncheck/cmd/cdncheck@latest go install -v github.com/projectdiscovery/tlsx/cmd/tlsx@latest go install -v github.com/ffuf/ffuf@latest go install github.com/OJ/gobuster/v3@latest go install -v github.com/projectdiscovery/dnsx/cmd/dnsx@latest -
Run ExternalAttacker-App.py
python ExternalAttacker-App.py # Access http://localhost:6991 -
Configure the MCP Server
"mcpServers": { "ExternalAttacker-MCP": { "command": "python", "args": [ "<Your_Path>\\ExternalAttacker-MCP.py" ] } }
🚀 Usage
Example queries you can ask through the MCP:
- "Scan example.com for subdomains"
- "Check open ports on 192.168.1.1"
- "Analyze HTTP services on test.com"
- "Check if domain.com uses a CDN"
- "Analyze SSL configuration of site.com"
- "Fuzz endpoints on target.com"
📜 License
MIT License
🙏 Acknowledgments
- The ProjectDiscovery team for their excellent security tools
- The MCP community for advancing AI-powered tooling
Note: This is a security tool. Please use responsibly and only on systems you have permission to test.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.