Tagged: MCP
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Ansible Deep Dive Part 13: Does Ansible Still Matter in an MCP/AI World?
Part 13, the closing piece: if an AI agent can SSH in and fix things itself, do playbooks, idempotency, and config management still matter? A case for yes — argued through the same MCP server that writes this very site.
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AI Part 8: Kali 2026.2's Nine New Tools, and the MCP Server With 150 More Behind It
Kali 2026.2 shipped nine new tools, one an AI CLI by default. I installed and ran every one I could in a rootless sandbox, then looked behind the curtain at a 17,000-line MCP server wrapping 150+ tools, and Kali's own local-LLM stack. No fabricated output.
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AI Part 9: From Draft-Only to Whole-Site — the v2.4 Tool Surface and the Rails Behind It
Parts 7 and 8 went out to other people's tool servers. This one comes home. v2.4 turns my blog's MCP server from a draft-publishing surface into one that can read, grep, write, and illustrate the whole site — and the interesting part was never the tools. It was the guardrails.
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AI Part 7: When an LLM Gets Nmap and Metasploit as Tools
I wired an LLM into nmap and Metasploit against a deliberately vulnerable lab. The exploit worked — a real, server-verified root shell — but the sharper finding was the models themselves: a 7B fabricated its tool output wholesale, an 8B mangled its arguments, and only a 32B drove the tools honestly. No fabricated transcripts — the model's included.
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AI Part 1: Why I Gave Claude Write Access to My Site
A year ago I would have called this irresponsible. Today an MCP server lets Claude write to my site. The trust model isn't "I trust the model" — it's "I trust the blast radius".
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AI Part 2: The Minimum Viable MCP Server
A personal MCP server is a tiny HTTP service. The spec accommodates a lot of complexity that, if you're the only user, you can stop building. Here's the inventory of what I have running, and what I deliberately left out.
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AI Part 3: Designing Tools for an LLM, Not for Yourself
The verb in the tool name is the most important part. Descriptions answer the questions a chooser asks, not the questions a maintainer asks. Allowlists fail closed; blocklists fail open. Error messages are also instructions.
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AI Part 4: Safety Rails — Allowlists, Atomic Writes, Audit Logs, Rollback
About two hundred lines of code, none of them clever, all of them the reason I sleep fine with the service running. Allowlists, atomic writes, an audit log, and a manual rollback path.
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AI Part 5: Prompt-Driven Authoring in Practice
What's it actually like to use? The honest answer, including where the loop is tight, where it's still clumsy, and the three things I'd warn anyone trying this.
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AI Part 6: Connector Quirks, Cache Traps, and What I'd Do Differently
Six months in. The cache layer you don't see, OAuth refresh edge cases, and the short list of decisions I'd make differently if I were doing this again from scratch.