by Wh0am123
MCP configuration to connect AI agent to a Linux machine.
# Add to your Claude Code skills
git clone https://github.com/Wh0am123/MCP-Kali-ServerMCP Kali Server (MKS) is a lightweight API bridge that connects MCP clients (e.g: Claude Desktop or 5ire) to the API server which allows executing commands on a Linux terminal.
This MCP is able to run terminal commands as well as interacting with web applications using:
Dirbenum4linuxgobusterHydraJohn the RipperMetasploit-FrameworkNiktoNmapsqlmapWPScanAs a result, this is able to perform AI-assisted penetration testing and solving CTF challenges in real time.
👉 How MCP is Revolutionizing Offensive Security
The goal is to enable AI-driven offensive security testing by:
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curl, nmap, ffuf, etc.) and receive structured outputs.Here are some example (using Google's AI gemini 2.0 flash):
https://github.com/user-attachments/assets/dc93b71d-9a4a-4ad5-8079-2c26c04e5397
https://github.com/user-attachments/assets/3ec06ff8-0bdf-4ad5-be71-2ec490b7ee27
curl and any other tool AI the needs.sudo apt install mcp-kali-server
kali-server-mcp
Otherwise for bleeding edge:
git clone https://github.com/Wh0am123/MCP-Kali-Server.git
cd MCP-Kali-Server
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
./server.py
Command Line Options:
--ip <address>: Specify the IP address to bind the server to (default: 127.0.0.1 for localhost only)
127.0.0.1 for local connections only (secure, recommended)0.0.0.0 to allow connections from any network interface (very dangerous; use with caution)--port <port>: Specify the port number (default: 5000)--debug: Enable debug mode for verbose loggingExamples:
# Run on localhost only (secure, default)
./server.py
# Run on all interfaces (less secure, useful for remote access)
./server.py --ip 0.0.0.0
# Run on a specific IP and custom port
./server.py --ip 192.168.1.100 --port 8080
# Run with debug mode
./server.py --debug
This can be local (on the same Kali machine) or remote (another Linux machine, Windows or macOS).
If you're running the client and server on the same Kali machine (aka local), run either:
## OS package
kali-server-mcp --server http://127.0.0.1:5000
# ...OR...
## Bleeding edge
./client.py --server http://127.0.0.1:5000
If separate machines (aka remote), create an SSH tunnel to your MCP server, then launch the client:
## Terminal 1 - Replace `LINUX_IP` with Kali's IP
ssh -L 5000:localhost:5000 user@LINUX_IP
## Terminal 2
git clone https://github.com/Wh0am123/MCP-Kali-Server.git
cd MCP-Kali-Server
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
./client.py --server http://127.0.0.1:5000
If you're openly hosting the MCP Kali server on your network (server.py --IP...), you don't need the SSH tunnel (but we do recommend it!)
NOTE: ⚠️(THIS IS STRONGLY DISCOURAGED. WE RECOMMEND SSH)⚠️.
./client.py --server http://LINUX_IP:5000
Edit:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonpython3 /absolute/path/to/client.py --server http://LINUX_IP:5000 and it will automatically generate the needed configuration files.There are more possibilities than described since the AI model can now execute commands on the terminal. Here are some examples:
Memory forensics using Volatility
Disk forensics with SleuthKit
This project is intended solely for educational and ethical testing purposes. Any misuse of the information or tools provided — including unauthorized access, exploitation, or malicious activity — is strictly prohibited.
The author assumes no responsibility for misuse.