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Free Plugin by onevteam v1.1.1

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.

One-V LLM Serve

The facts

Rating
4.5★ from 8
Active installs
10+
Price
Free
Last updated
14 Jul 2026
Added
May 2026
Requires WP
6.2
Tested up to
WP 7.0.4
Requires PHP
8.0
Downloads
631

Our analysis

AI-assisted

One-V LLM Serve is a WordPress plugin that provides a Markdown version of every public page on your site at the same URL with a .md extension. It requires no configuration and is designed to enhance compatibility with AI systems that prefer Markdown over HTML for parsing content.

The plugin generates a clean Markdown file containing a YAML frontmatter block, page title, headings, and body text, stripping unnecessary elements from the HTML. It also includes features for analytics and tracking AI interactions, making it suitable for users interested in optimising their content for AI consumption.

Best for: This plugin is best suited for website owners looking to optimise their content for AI systems and improve SEO.

What it does well

  • Zero configuration required for Markdown endpoints
  • Configurable YAML frontmatter for each page
  • Integrates with both Classic Editor and Gutenberg
  • Tracks AI analytics with detailed event logging
  • Supports custom post types and taxonomy archives

Where it falls short

  • Limited information on specific use cases or user feedback

Verdict

One-V LLM Serve offers a straightforward solution for generating Markdown versions of WordPress pages, making it a useful tool for those focused on AI content generation and tracking.

From the developer

onevteam's own description of One-V LLM Serve, lightly tidied.

One-V LLM Serve makes every public page on your WordPress site available as clean Markdown at the same URL with a .md extension — zero configuration required.

https://example.com/about/      ← HTML page for humans
https://example.com/about.md    ← clean Markdown for AI

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.

Core features

  • Zero-config Markdown endpoint for every public post, page, and custom post type
  • YAML frontmatter with configurable fields (title, date, modified, url, description, image, tags, categories, lang, type)
  • /llms.txt discovery file at the site root following the llmstxt.org convention
  • Taxonomy archives as Markdown — /category/news.md, /tag/foo.md, custom taxonomies
  • ?format=markdown query parameter as an alternative to the .md URL on any singular page
  • Per-post exclude via a sidebar checkbox on the post editor
  • Works with Classic Editor and Gutenberg via the the_content filter
  • ACF integration — opt-in per-post: pick which text, textarea, WYSIWYG, URL, email, or link fields to append below the body
  • 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.
  • Browser-bucket sub-classification — anything that looks like a browser visit gets split into four kinds based on the Sec-Fetch-Site, Sec-Fetch-User, and Sec-CH-UA 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 — requests, httpx, 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.

Discoverability

  • Link: rel="alternate"; type="text/markdown" HTTP header on every HTML page
  • <link rel="alternate"> tag in <head> for HTML-based discovery
  • Allow: /*.md$ directive in robots.txt
  • CORS Access-Control-Allow-Origin: * on .md and /llms.txt so browser-based AI clients can fetch them

Operations

  • Transient caching with automatic invalidation on save_post, on ACF field value saves, on any ACF field group change, and on plugin settings save
  • “Clear cache” button in the settings page
  • Admin notice on fallback HTTP fetch failures
  • “Settings” link next to the plugin row in Plugins screen
  • “View .md” row action in the Posts and Pages list tables

Developer hooks

  • ovls_markdown filter for the final Markdown output
  • ovls_frontmatter filter for adding, removing, or modifying frontmatter fields
  • ovls_content_queries filter for the HTML extraction XPath cascade

How it works

Each request to /about.md is captured by a WordPress rewrite rule and routed through the plugin’s content generator. The generator runs the post through apply_filters( 'the_content', ... ) — 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 league/html-to-markdown, then cached in a WordPress transient.

The cache is invalidated automatically on save_post, on ACF field/group changes, and whenever plugin settings are saved. A manual Clear cache button is also available on the settings page.

Access methods

Read the full description on the official page →

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