For SaaS

Agent readiness for SaaS

A growing share of software discovery now runs through an AI assistant answering "what tool should I use for X", not a search results page. If your docs and your API are unreadable to that assistant, you are not in the running, regardless of how good the product is.

Why it matters

Gartner predicted in February 2024 that traditional search volume would fall 25% by 2026 as AI chatbots and virtual agents substitute for search.
Source: Gartner, Feb 2024 That shift is why your docs and product pages increasingly get read by assistants instead of people clicking through: when someone asks an AI assistant to recommend a tool for a job your product does, the assistant is reading pages, not opinions, so a product whose docs and marketing pages are markdown-friendly and well-structured is easier to cite accurately than one buried behind client-rendered JavaScript with no llms.txt to point at what matters.

Cloudflare measured how much AI crawlers read versus how much traffic they send back, in July 2025 data: Anthropic's crawler fetched around 38,000 pages for every visit it referred, OpenAI's around 1,100, classic Google search about 5.
Source: Cloudflare, Aug 2025 Assistants read enormously more than they refer, so the exposure that matters is not how much traffic comes back, it is whether what they read about you is your own clean, structured content or someone else's summary of you.

Agentic tool use is the second, increasingly common front. If your product has an API, exposing it as an MCP server means an agent can discover and call your tools directly instead of a developer hand-writing an integration. A SaaS product with an MCP server card at a well-known location is legible to that whole category of AI-native usage; one without it is invisible to it.

What we implement

  • agents.md describing your product, your API, and where the real documentation lives
  • llms.txt and llms-full.txt structured around your docs, not your marketing copy
  • An MCP server card at /.well-known/mcp.json if you have an API worth exposing as tools
  • SoftwareApplication structured data (JSON-LD) on your marketing and pricing pages
  • Content negotiation so docs served as markdown when an agent asks for it, not just HTML

Expected outcome

This makes your product readable and eligible for AI-assisted discovery and agentic tool use: an assistant summarizing options for a user can accurately describe what you do, and an agent looking for a tool to call can find and use yours. It does not guarantee adoption or that any specific assistant recommends you over a competitor, only that the technical door is open.

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