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One-V LLM Serve makes every public page on your WordPress site available as clean Markdown at the same URL with a <code>.md</code> extension — zero configuration required.
<pre><code>https://example.com/about/ ← HTML page for humans
https://example.com/about.md ← clean Markdown for AI
</code></pre>
AI systems — ChatGPT, Perplexity, ClaudeBot, Google AI Overviews, and most RAG pipelines — parse Markdown far more efficiently than HTML. When these systems encounter an HTML page, they must strip navigation, headers, footers, sidebars, scripts, and tracking pixels before they can read the actual content. This noise introduces errors, increases token cost, and leads to lower-quality outputs.
The Markdown file contains a configurable YAML frontmatter block followed by the page title, headings in correct hierarchy, and the body text. Nothing else.
<h4>Core features</h4>
<ul>
<li>Zero-config Markdown endpoint for every public post, page, and custom post type</li>
<li>YAML frontmatter with configurable fields (<code>title</code>, <code>date</code>, <code>modified</code>, <code>url</code>, <code>description</code>, <code>image</code>, <code>tags</code>, <code>categories</code>, <code>lang</code>, <code>type</code>)</li>
<li><code>/llms.txt</code> discovery file at the site root following the <a href="https://llmstxt.org" rel="nofollow ugc">llmstxt.org</a> convention</li>
<li>Taxonomy archives as Markdown — <code>/category/news.md</code>, <code>/tag/foo.md</code>, custom taxonomies</li>
<li><code>?format=markdown</code> query parameter as an alternative to the <code>.md</code> URL on any singular page</li>
<li>Per-post exclude via a sidebar checkbox on the post editor</li>
<li>Works with Classic Editor and Gutenberg via the <code>the_content</code> filter</li>
<li>ACF integration — opt-in per-post: pick which text, textarea, WYSIWYG, URL, email, or link fields to append below the body</li>
<li>Filterable AI analytics — per-hit events with full denormalised dimensions (UA bucket, referrer host, language, post type, response code), sticky filter bar that drives every chart and table live, six KPI tiles, a stacked-area time chart, three composition donuts (UA bucket / referrer source / language), four Top tables, a User-Agent classifier transparency table, and a Recent Activity stream. Referrers are tracked by hostname only — paths and query strings are stripped before storage so no PII is retained. Forward-compatible classification: when the bot or referrer catalogue is updated in a future release, historical rows are reclassified automatically — no Reset Analytics required.</li>
<li>Browser-bucket sub-classification — anything that looks like a browser visit gets split into four kinds based on the <code>Sec-Fetch-Site</code>, <code>Sec-Fetch-User</code>, and <code>Sec-CH-UA</code> request headers a real browser sends: verified user (top-level navigation triggered by a click or address-bar Enter in a recognised browser), headed agent (real Chromium driven programmatically — Playwright, Puppeteer, Selenium), script agent (bare HTTP client imitating a browser UA — <code>requests</code>, <code>httpx</code>, LangChain, custom agents), spoofer (UA shape that no real browser would emit, like modern Chrome with a non-reduced UA). Visible as a stacked-bar breakdown on the User-Agents subpage so you can see at a glance how much of your “human” traffic is actually automation, and rendered inline as colour-coded slugs on every browser-bucket row in the Recent Activity table on the Analytics page. Detection is server-side fingerprinting of the request itself — no cookies, no JS, no IP.</li>
</ul>
<h4>Discoverability</h4>
<ul>
<li><code>Link: rel="alternate"; type="text/markdown"</code> HTTP header on every HTML page</li>
<li><code><link rel="alternate"></code> tag in <code><head></code> for HTML-based discovery</li>
<li><code>Allow: /*.md$</code> directive in <code>robots.txt</code></li>
<li>CORS <code>Access-Control-Allow-Origin: *</code> on <code>.md</code> and <code>/llms.txt</code> so browser-based AI clients can fetch them</li>
</ul>
<h4>Operations</h4>
<ul>
<li>Transient caching with automatic invalidation on <code>save_post</code>, on ACF field value saves, on any ACF field group change, and on plugin settings save</li>
<li>“Clear cache” button in the settings page</li>
<li>Admin notice on fallback HTTP fetch failures</li>
<li>“Settings” link next to the plugin row in Plugins screen</li>
<li>“View .md” row action in the Posts and Pages list tables</li>
</ul>
<h4>Developer hooks</h4>
<ul>
<li><code>ovls_markdown</code> filter for the final Markdown output</li>
<li><code>ovls_frontmatter</code> filter for adding, removing, or modifying frontmatter fields</li>
<li><code>ovls_content_queries</code> filter for the HTML extraction XPath cascade</li>
</ul>
<h4>How it works</h4>
Each request to <code>/about.md</code> is captured by a WordPress rewrite rule and routed through the plugin’s content generator. The generator runs the post through <code>apply_filters( 'the_content', ... )</code> — the same pipeline WordPress uses on the front end — so Classic Editor, Gutenberg, and shortcodes all work without separate code paths. The rendered HTML is converted to Markdown via <code>league/html-to-markdown</code>, then cached in a WordPress transient.
The cache is invalidated automatically on <code>save_post</code>, on ACF field/group changes, and whenever plugin settings are saved. A manual Clear cache button is also available on the settings page.
<h4>Access methods</h4>
There are three equivalent ways to request the Markdown version of a page:
<ul>
<li><code>.md</code> extension — <code>https://example.com/about.md</code></li>
<li><code>?format=markdown</code> query — <code>https://example.com/about/?format=markdown</code></li>
<li><code>Link: rel="alternate"</code> header — returned by every HTML page</li>
</ul>
The <code>.md</code> URL is the recommended canonical form.
<h4>ACF integration</h4>
When <a href="https://www.advancedcustomfields.com/" rel="nofollow ugc">Advanced Custom Fields</a> is active, ACF field rendering is opt-in at two levels:
<ol>
<li>Site defaults per post type — at Settings → One-V LLM Serve → ACF Defaults, tick fields that should be appended to every post of a given post type.</li>
<li>Per-post override — the One-V LLM Serve metabox on each post editor lists every supported ACF field applicable to that post. Tick fields to replace the site defaults for that one post.</li>
</ol>
Supported ACF types: <code>text</code>, <code>textarea</code>, <code>wysiwyg</code>, <code>url</code>, <code>email</code>, <code>link</code>. Each selected field is rendered under a <code>## Field Label</code> heading. Empty fields are skipped.
<h3>Disclaimer</h3>
This plugin is provided “as is”, without warranty of any kind, express or implied, in accordance with the GNU General Public License v2 or later. The authors and contributors are not liable for any direct, indirect, incidental, special, or consequential damages — including but not limited to data loss, lost profits, business interruption, search-ranking changes, or third-party claims — arising from the use of, or inability to use, this software, even if advised of the possibility of such damages.
By installing and activating the plugin you acknowledge that:
<ul>
<li>You are responsible for testing the plugin in a staging environment before deploying to production.</li>
<li>You are responsible for the content this plugin exposes as Markdown — <code>.md</code> URLs and <code>/llms.txt</code> serve the same content as their HTML counterparts and are intended to be crawled and consumed by AI systems and third-party LLMs.</li>
<li>The plugin does not transmit data to any external service. All Markdown generation, caching, and file writes happen on your own server.</li>
</ul>
Nothing in this disclaimer is intended to exclude or limit liability for matters that cannot lawfully be excluded under the consumer-protection laws of your jurisdiction. For the full legal terms see the GPLv2 license at <a href="https://www.gnu.org/licenses/gpl-2.0.html" rel="nofollow ugc">https://www.gnu.org/licenses/gpl-2.0.html</a>.

One-V LLM Serve

Serve clean Markdown versions of every public page at the same URL with a .md extension for AI crawlers, LLMs, and GEO optimization.

David Perez

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Alex Brea

Knowledge Base Chatbot helps you curate the exact content you want to use as a “knowledge base” and generates a single Markdown file (<code>llm-knowledge-chatbot.md</code>) that can be consumed by an external chatbot or LLM pipeline.
From the WordPress admin, you can:
<ul>
<li>Select content from any public post type that is available in the admin (Pages, Posts, and most custom post types).</li>
<li>Add selected items to a curated list.</li>
<li>Reorder the list via drag & drop.</li>
<li>Regenerate the Markdown file at any time (it is also regenerated automatically after adding/removing items).</li>
</ul>
The generated file is saved in your WordPress root folder and can be accessed via a public URL such as: 
 https://example.com/llm-knowledge-chatbot.md

Knowledge Base Chatbot

Generate a Markdown knowledge base file from selected WordPress content (pages, posts, and CPTs) to power an external chatbot/LLM workflow.

One-V LLM Serve vs Knowledge Base Chatbot