MCP + Kali Linux : Automatiser le pentest avec son IA locale (tuto complet)

MCP + Kali Linux : Automatiser le pentest avec son IA locale (tuto complet)

by Michel Kartner

Applied Sciences & Engineering Computing & Cybersecurity UComputing and Information TechnologyURComputer security
🎙 Michel Kartner 👥 194K 📅 June 8, 2026 ⏱ 30 min 👁 7K 📄 tutorial 🧭 2026-08-02
Available in: English (current) Français

Keywords

MCPKali LinuxAI automationpentestingAnythingLLM

Summary

This tutorial by Michel Kartner demonstrates how to automate penetration testing tasks using a local AI assistant (AnythingLLM) integrated with Kali Linux and various MCP (Model Context Protocol) servers. The video begins with a demo showing the AI controlling a browser and performing a port scan on the author’s website. It then explains how to configure agent skills in AnythingLLM, including file access, document creation, and graph generation. The author shows how to download and install agent flows from the AnythingLLM hub, such as a Hacker News headline viewer, and how to create custom flows. He also demonstrates connecting data sources like GitHub repositories (e.g., OWASP CheatSheetSeries) to the AI’s RAG memory for enhanced knowledge. The core of the video focuses on integrating MCP servers: Shodan for network intelligence, Playwright for browser automation, and a Kali Linux MCP server for executing commands. The author walks through setting up each MCP server, configuring API keys, and using the AI to perform tasks like scanning a target with Nmap, automating browser interactions, and running a pentest on DVWA. The video concludes with an analysis of the generated pentest report. The tutorial is practical and hands-on, providing step-by-step instructions and links to the necessary tools and repositories.

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Critical Evaluation

The video provides a comprehensive and practical tutorial on integrating MCP with a local AI to automate pentesting tasks. The author demonstrates a clear workflow, from configuring agent skills to connecting external tools via MCP servers. The information is presented in a structured manner, with chapters and clear explanations. The technical depth is appropriate for an audience with some familiarity with cybersecurity and AI tools. The author’s approach is methodical, and he provides real-world examples, such as using Shodan to scan a target and automating browser interactions with Playwright. The sources cited are reputable open-source projects and official documentation, which enhances the credibility of the content. However, the video is a tutorial and does not delve into the theoretical underpinnings of MCP or the security implications of using such automation. The author’s claims about the AI’s capabilities are based on personal experience and may not be generalizable. Additionally, the video does not address potential risks, such as the AI misinterpreting commands or the security of the MCP servers themselves. The adéquation between the title and content is excellent, as the video fully delivers on its promise of a complete tutorial. The presentation is engaging, with a clear demonstration of the AI’s actions. The author also provides additional resources, such as links to the OWASP CheatSheetSeries and PayloadsAllTheThings, which are valuable for pentesters. Overall, the video is a valuable resource for those looking to leverage AI in their pentesting workflows, but it should be complemented with a deeper understanding of the underlying technologies and security considerations.

255 words

Title / Content Match

The title accurately reflects the content: the video demonstrates how to use MCP with Kali Linux to automate pentesting with a local AI, providing a complete tutorial.

Quality & Reliability

7/10

The tutorial is practical and hands-on, demonstrating real configurations and integrations. The author provides links to official repositories and tools, enhancing credibility. However, the video is a tutorial and does not include rigorous scientific validation or peer-reviewed sources, and the author's claims about AI capabilities are anecdotal.

Chapters

Cited Sources

Concurring Sources

  • AnythingLLM — The tool is presented as the main platform for local AI agents, and the video demonstrates its features.
  • MCP Shodan Server — The video shows how to set up this MCP server to query Shodan, aligning with the repository's purpose.
  • Playwright MCP Server — The video demonstrates browser automation using this MCP server, consistent with its functionality.
  • Kali Linux MCP Server — The video shows how to use this MCP server to execute Kali Linux commands, matching its intended use.

External References

Contribution & Novelties

This video provides a practical guide to integrating MCP with a local AI for pentesting, demonstrating a novel workflow that combines AI automation with traditional security tools. It offers a step-by-step approach to setting up MCP servers for Shodan, Playwright, and Kali Linux, and shows how to use them through a chat interface. The video also highlights the use of RAG to import security knowledge bases like OWASP CheatSheetSeries, enhancing the AI’s capabilities.

Pour aller plus loin :

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Radar Profile

The radar profile shows high scores in quantity of information and technical level, indicating a content-rich tutorial with substantial technical depth. The quality of information and global reliability are slightly lower, reflecting the tutorial's practical nature and reliance on anecdotal evidence rather than formal scientific validation.

Reliability 7/10