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llms.txt status in 2026 — from 15 sites to 10% adoption among 300K domains. Skeptics vs proponents arguments, three development scenarios

Jeremy Howard (Answer.AI / fast.ai) proposed llms.txt in September 2024. The idea: give LLMs a structured Markdown file instead of forcing them to parse HTML.

llms.txt is not a formal standard. No W3C or IETF process. It’s a community-driven convention, similar to robots.txt in 1994 — de facto first, then (28 years later) RFC 9309.

Repository AnswerDotAI/llms-txt: 2,191 stars, 118 forks, 65 open issues, Apache-2.0 license (as of January 2026).

PeriodNumber of SitesSource
February 2025~15early adopters
May 2025~105llms-txt-hub
October 2025844,000+ALLMO.ai analysis
January 202610.13% of 300K domainsSE Ranking

The llms-txt-hub directory (732 stars, 381 forks) is the largest llms.txt site catalog.

CategoryExamples
AI/MLAnthropic, Hugging Face, Cohere, CrewAI, LangChain
DevToolsCloudflare, Stripe, Vercel, Astro, Resend
CMS/No-codeYoast, Zapier, Make, Activepieces
DocumentationMDN, LangChain, Supabase, Turso
DatabasesDuckDB, Upstash, Turso

Adoption is growing, but evidence of direct impact on AI citations remains mixed.

John Mueller (Google), June 2025:

“No AI system uses llms.txt to generate answers.”

OtterlyAI (90-day experiment): 0.1% of AI crawler requests went to /llms.txt — 84 visits over 3 months vs 265 average per page. AI bots do visit, but rarely.

SE Ranking (2026): analyzing 300K domains found no correlation between having llms.txt and AI citation frequency.

Vercel: 10% of new signups come from ChatGPT. Structured content works.

Dev5310: Google AI Mode cited a site with llms.txt on day one after publishing.

Ecosystem: 14+ generators, plugins for WordPress (5+), MkDocs, Docusaurus, Nuxt, Astro, Discourse. Developers are voting with code.

Skeptics evaluate llms.txt as a standalone signal for AI search. Proponents see broader use cases: MCP, RAG, developer experience, AI assistants in IDEs.

AI providers (OpenAI, Google, Anthropic) begin formally supporting llms.txt. The file becomes a standard part of the SEO stack — like sitemap.xml.

Model Context Protocol (Anthropic → Linux Foundation) absorbs llms.txt use cases. The file remains as a lightweight discovery layer for MCP servers.

AI models become smart enough to parse any content. llms.txt remains a niche solution for documentation.

Creating llms.txt is a low risk, low cost decision:

  • Time: 15-30 minutes for manual creation, 0 minutes with auto-generation
  • Risks: no negative side effects
  • Value even without AI search: MCP integration, RAG pipelines, context for AI assistants, structured documentation

If you maintain documentation or a technical site — implementation is justified. Cost is minimal, potential is significant.


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