Why this site talks to agents

If you're reading this in a browser, you're standing in mlzen's front door. There's a second one, around the back, and it's not an afterthought: this site also publishes for AI agents, deliberately and openly, as a real audience alongside you.

Concretely, that means three things. Every article on this site can hand a plain-text markdown version of itself to anything that asks for one, instead of a page of HTML built for a browser. The site runs a small server that lets an AI assistant look up, search, and read mlzen's posts directly, the way it might use any other tool. And the site publishes a short file at its root that tells a language model what mlzen is and where to find everything on it. None of this is exotic. It's closer to how a print magazine used to mail a subscriber a copy while a librarian requested a separate one for the archive: same content, different delivery, built for a different kind of reader. Here's what each piece actually is, and why it's spreading across the web right now.

Markdown on request

When your browser asks for a page, it sends a header (a small line of metadata attached to the request) saying roughly "send me HTML, I know how to display that." An AI agent fetching the same page often doesn't want the HTML at all. It doesn't need the navigation bar, the footer, or the styling markup; it wants the words. So it can send a different header, Accept: text/markdown, and a well-built site can notice that and respond with clean markdown instead: just the title, the text, the structure, none of the wrapper.

This pattern has a name, content negotiation, and it's old. It's how the web has always let one URL serve different formats to different clients. What's new is using it specifically for agents. Vercel, the company behind a popular web hosting platform, published a detailed writeup in February 2026 showing exactly this: sites answering the markdown-flavored request with a rewritten route, plus giving every page a matching .md address as a fallback for clients that can't set custom headers at all. mlzen does both. Ask for /briefs/2026-w29 with Accept: text/markdown, or just go to /briefs/2026-w29.md, and you get the same brief, agent-ready, with no HTML to strip out first.

A server built for questions, not clicks

The second piece is more unusual. mlzen runs a small server at /mcp that speaks the Model Context Protocol, or MCP: an open standard, originally published by Anthropic, for letting an AI assistant call a defined set of tools against a service. Instead of an agent scraping mlzen's pages and guessing at their structure, it can call a function like "list the recent briefs tagged cybersecurity" or "get me the full text of this post" and get a clean, structured answer back. It's the same idea as an API, which software has used to talk to other software for decades. MCP just standardizes the shape of that conversation, so an AI model can use it without a developer writing custom integration code for every single site it visits.

The current version of the protocol favors a transport called Streamable HTTP: one endpoint that can take a request and, if needed, keep a connection open to stream a longer response back, tracked with a session ID so the conversation doesn't get lost between calls. That's plumbing detail, but it matters for one reason: it means an agent's connection to mlzen behaves predictably, the same way your browser's connection to any website does, rather than being some bespoke thing every site reinvents differently.

The one-page map

Third: mlzen publishes an llms.txt file. This is about as simple as web standards get: a plain markdown file at the site's root with a title, a short description, and a list of links to the important pages, meant to give a language model a fast, honest map of the site instead of making it guess from a homepage designed for human eyes. The format was proposed in 2024 by Jeremy Howard, and it's since been picked up widely enough that it's become a reasonable default for any site that wants to be legible to an AI reader quickly. Worth being honest about its limits: nobody has shown that having an llms.txt file changes whether a model gets trained on your content, or whether search engines rank you differently. What it does is make the site's own structure explicit and cheap to parse, which is a real, if modest, benefit on its own.

Why bother proving who's asking

Publishing for agents raises an obvious follow-up question: how does a site know it's actually talking to a well-behaved agent, and not something pretending to be one? This is where the plumbing gets genuinely new. The IETF, the standards body that has defined most of the web's core protocols, has an active working group called Web Bot Auth, building on an existing signature standard (RFC 9421) to let an automated client cryptographically sign its own requests. Done well, a server can verify that a request really did come from the agent it claims to be, the same way a signed letter is harder to forge than an unsigned one, instead of relying on the User-Agent string, which any script can just type in by hand.

Cloudflare, which sits in front of a very large share of the web's traffic, has built support for verifying these signed requests at the edge. It has also introduced a "Content Signals" addition to the humble robots.txt file, letting a publisher say, distinctly, whether it's fine with a page being used for search, for answering a live question, or for training a future model. Those are three different permissions that used to be one blunt "allow or disallow." Cloudflare has since started scoring public sites on how "agent ready" they are: whether the markdown routes exist, whether an MCP server is discoverable, whether the signals are set. That's a genuinely new kind of audit, one that didn't need to exist five years ago.

What this adds up to

None of these pieces, alone, is dramatic. Put together, they describe something real: the web is quietly building a second, machine-readable version of itself, running alongside the one built for browsers, with its own emerging conventions for format, discovery, and trust. mlzen exists to write clearly about that kind of shift for people, and it seemed dishonest to write about a machine-readable web while only publishing for humans. So this site does both, in the open, on purpose. You're welcome at either door.

Sources

Vercel: Making agent-friendly pages with content negotiation

Model Context Protocol: Transports (spec rev 2025-06-18)

llms.txt specification

IETF: Web Bot Auth working group

Cloudflare: Verifying signed agents

Cloudflare: Content Signals Policy

Cloudflare: Agent Readiness