Picking an llms.txt tool depends on your stack, not on which is "best".

Best for: WordPress sites already on AIOSEO

One-click llms.txt generation inside the AIOSEO plugin. The cleanest WP path for sites already on AIOSEO. Auto-respects existing noindex / nofollow settings, which most standalone WP generators do not.

Best for: WordPress sites already on Yoast (and Shopify, as of March 2026)

Free in the regular Yoast plugin, no Premium upgrade needed. Yoast SEO for Shopify added the same toggle in March 2026 - the main SEO-suite route on Shopify, though standalone llms.txt generator apps also exist in the Shopify App Store.

Best for: WordPress sites on Rank Math

Equivalent toggle inside the Rank Math plugin. Slightly more configurable than Yoast on which post types feed the file. If Rank Math is already installed, do not bolt on a second generator.

Best for: Large content libraries that need curation, not just dump

WordLift will analyse content and pick the strongest evergreen URLs rather than listing everything. Useful if your site has thousands of posts and you do not want every category page in the file. The free standalone generator is fine; the $879/mo plan is only worth it for enterprise content ops.

Best for: WordPress sites that need both files and are not on AIOSEO / Yoast / Rank Math

One of the few WP plugins that ships llms-full.txt as well as llms.txt. Worth knowing because most WP options skip llms-full.txt entirely and that is the file AI agents fetch more often (see Profound data below).

Best for: Hosted documentation, zero-config setup

Auto-generates llms.txt, llms-full.txt and a .md version of every page with no config. If your docs are already on Mintlify, there is literally nothing to do. Mintlify also publish the strongest comparison piece on the wider docs-platform landscape.

Best for: API documentation where you need bot-specific delivery

Auto-generates both files, detects LLM bot traffic, serves markdown instead of HTML to those bots (Fern claim 90%+ token reduction). Content tags like <llms-only> and <llms-ignore> give per-block control. Heavier price tag, but the only platform offering analytics by LLM provider.

Best for: Teams already on GitBook for docs

One-click toggle exposes both files. No granular content controls, no LLM-specific analytics. Solid low-friction option if GitBook is where the docs already live.

Best for: Interactive API docs with basic llms.txt

Toggle on in settings. Append .md to any page URL for a markdown version. Does NOT generate llms-full.txt and offers no AI-specific analytics. Fine if you already use ReadMe; not a reason to switch to it.

Best for: OpenAPI-first docs

Toggle-based llms.txt support. No llms-full.txt. Worth knowing: Redocly have publicly argued llms.txt is overhyped and are putting their effort into MCP server support instead. Picked because of OpenAPI strength, not because of AI features. If AI discoverability is your reason for choosing a docs platform, Mintlify, Fern or GitBook all do more.

Best for: OpenAPI-first teams happy to wire the file up themselves

Generates interactive API references from OpenAPI specs and has tooling for converting them to LLM-readable markdown. No automatic llms.txt generation though - you configure the routes and keep the file in sync yourself. Building blocks, not a toggle.

Best for: Next.js docs where you own the code

Docs framework for Next.js. You can add middleware that detects AI agents and serves markdown, but llms.txt and llms-full.txt need custom route handlers you build and maintain. Full control, zero automation. Fine if that trade suits your team.

Best for: Docusaurus-based docs sites

Generates llms.txt, llms-full.txt and per-page .md files. Batch processing handles large sites. Install via npm, configure in docusaurus.config.js. The most complete of the three community plugins.

Best for: Astro Starlight documentation

Generates llms.txt, llms-full.txt and a llms-small.txt for cheaper token contexts. Per-page .md exposure. Active, well-maintained plugin.

Best for: Python (MkDocs) or Vue (VitePress) docs

mkdocs-llmstxt and vitepress-plugin-llms both generate llms.txt and llms-full.txt during build. Hugo has no dedicated plugin but its output format system makes it a 30-minute custom config job. Eleventy (eleventy-plugin-llms-txt) and Gatsby (gatsby-plugin-llms-txt) have plugins too, but both are llms.txt only.

Best for: Python projects documenting with Sphinx

sphinx-llms-txt generates llms.txt with zero configuration. If the docs are hosted on Read the Docs, the platform also serves llms.txt and llms-full.txt from your default version automatically - no plugin needed. The lowest-effort option on this whole list for Python docs.

Best for: Laravel and PHP apps wanting programmatic generation

stolt/llms-txt-php. Use when llms.txt needs to update on content changes (CMS-driven sites, headless setups) rather than being a static file. Stable, well-tested, low ceremony.

Best for: Quick one-off llms.txt from any URL

Crawls a domain, uses gpt-4o-mini to extract titles and descriptions, produces both llms.txt and llms-full.txt. Best starter generator for sites not on a platform that auto-builds the file. Expect to hand-edit the output (auto-crawls always over-include).

Best for: Quick browser-based draft from a URL

No signup, paste a URL, edit in-browser, download. Output is a starter, not a finished file. Use it the same way you would use Firecrawl - draft, then curate.

Best for: Sitemap-driven generation with a built-in validator

Generates the file from your sitemap rather than a crawl, and bundles a validator plus an MCP converter in the same toolkit. The sitemap approach means it inherits whatever curation your sitemap already has - often a better starting draft than a raw crawl.

Best for: Catching malformed entries before you deploy

Independent validator at llmstxtvalidator.dev. Flags unsupported directives, broken absolute URLs, missing required fields. Always run a generated file through this before shipping it - especially the WordPress plugin outputs, which drift on edge cases.

Best for: Confirming the pages your llms.txt points at are actually AI-extractable

Not an llms.txt generator. Validates whether the pages your llms.txt curates have the schema and structure AI engines can extract from. Useful pair with whichever generator you pick - a tidy llms.txt pointing at extraction-hostile pages is wasted effort.