How to convert HTML to Markdown for AI applications
If your application already has HTML, you do not need to fetch the page a second time. Prepare the source once, convert it, and keep the result with the processing record.
Developer guide
Resource collection
Implementation and operations
Plan retrieval, content consistency, access policies and production checks for AI-readable website workflows.
About this collection
Choose an implementation by the responsibility it needs to serve. Search, acquisition, conversion, publication and application storage are different operations, even when one vendor offers several of them. These guides make those boundaries explicit and give web teams concrete acceptance questions.
Start with the public developer documentation when integrating Parse or Retrieve. Use the publishing setup guide for website delivery. The operational checklists here complement those contracts; they do not broaden endpoint behavior, grant access to private content or imply that changing a crawler label verifies its identity.
Implementation
1–17 of 17 resources
How to retrieve a webpage as Markdown for a RAG workflow
A URL is a starting point, not a complete knowledge pipeline. Acquire the eligible page, prepare its content, inspect the result and decide what your application should index.
Developer guide
Does AI receive the page your visitors see?
A website can look complete in a browser while important information is missing from its initial response.
Technical guide
Four files. Four different jobs.
Robots rules, sitemaps, llms.txt and Markdown solve different problems.
AI discovery guide
Audit HTML and Markdown delivery before testing AI answers
Before asking whether AI understands your website, establish which response your own test actually received.
Technical guide
Cloudflare Markdown for Agents: Implementation Decisions and Limitations
Enabling Markdown delivery is only one implementation decision. A responsible rollout also checks which pages qualify, what information survives and how existing website behavior is protected.
Implementation guide
Markdown Content Negotiation: A Cache and Response Validation Checklist
If one URL can produce both HTML and Markdown, the cache must not accidentally confuse the two. Here's how to turn that requirement into testable acceptance conditions.
Technical guide
HTML, Markdown and JSON-LD: How to Test Information Consistency
When a business publishes the same facts in multiple representations, they should tell a consistent story. That doesn't mean every format must contain the same fields.
Technical guide
Exa Search and AI-Readable Publishing: Two Different Parts of Retrieval
Finding information and publishing information are different responsibilities. Understanding that distinction helps teams build better AI retrieval workflows.
Architecture and workflows
You.com Search APIs and Publisher Content: Understanding the Retrieval Boundary
An AI application can search the web, extract a page and generate a cited answer. Those operations are related, but each produces a different kind of evidence.
Architecture and workflows
Exa vs You.com: Choosing a Web Retrieval API for an AI Application
Exa and You.com both support AI applications that need information from the web. The useful choice depends on the job your application must perform—not a generic ranking of the providers.
Developer comparison
How to Check Whether an AI Retrieval System Is Using Fresh Website Content
When an AI application returns outdated information, the first question is where the older version entered the workflow. A controlled freshness test helps narrow the possibilities.
Research methods
A Website Owner's Checklist for AI Crawler Access Policies
Before changing how AI crawlers access your website, decide which information should be public, which activities you want to permit and which resources require real access protection.
Technical governance
How to Distinguish Claimed AI Bot Identity From Verified Bot Traffic
A request carrying the name of an AI crawler is not automatically a verified request from that provider. Attribution requires evidence beyond the User-Agent string.
Technical verification
Designing an Approval Workflow for Content Published to AI Systems
When a business publishes information for AI systems to encounter, the important control is not merely who can edit the content. It is which exact claims were reviewed and authorized for publication.
Publishing governance
What Happens When AI-Readable Content Must Be Corrected or Withdrawn?
Publishing is not always the final step. When a public claim becomes wrong, the business needs a controlled way to correct or withdraw it—and a realistic understanding of what that correction can reach.
Operational recovery
Production Acceptance Tests for an AI-Readable Website
A website can pass a content audit and still fail during deployment. Production acceptance asks a different question: did the approved change go live without breaking the website or modifying unrelated state?
Production operations