---
title: Accessing documentation as Markdown
summary: null
url: https://www.fastly.com/documentation/reference/markdown
---

Most pages on the Fastly documentation site are available in Markdown format. This makes it easy for AI assistants, large language models (LLMs), agent frameworks, and developer tools to retrieve and use Fastly technical content without parsing HTML.

## Why Markdown?

HTML pages are optimized for humans using web browsers. They contain navigation, scripts, styles, and other structural markup that is noise for automated tools. Markdown gives you the same content in a format that is:

- **Compact:** stripped of navigation, scripts, and layout markup
- **Structured:** headings, code blocks, and tables are preserved with standard Markdown syntax
- **Machine-readable:** easy to tokenize, chunk, and embed for LLM pipelines
- **Copy-pasteable:** useful as context in prompts or as source material for tools

## Appending `.md` to any URL

The simplest way to access a page as Markdown is to append `.md` to any documentation URL:

| HTML page                                                                            | Markdown equivalent                                                                    |
| ------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------- |
| `https://www.fastly.com/documentation/guides/getting-started/domains/about-domains/` | `https://www.fastly.com/documentation/guides/getting-started/domains/about-domains.md` |
| `https://www.fastly.com/documentation/reference/vcl/functions/strings/regsuball/`    | `https://www.fastly.com/documentation/reference/vcl/functions/strings/regsuball.md`    |

## Sending an Accept header

You can also request Markdown by sending an `Accept: text/markdown` header with any GET request. The response will include a `Content-Type: text/markdown; charset=utf-8` header.

```bash
curl -H "Accept: text/markdown" https://www.fastly.com/documentation/guides/getting-started/domains/about-domains/
```

## Markdown for AI clients

Our site serves Markdown automatically to known AI user agents, including Claude, ChatGPT, Perplexity, and similar tools. These clients don't need to send an `Accept: text/markdown` header. The documentation site detects them and responds with Markdown by default.

If you are building an AI agent or tool that fetches Fastly documentation, you can rely on `.md` URLs or the `Accept` header for consistent Markdown responses regardless of the user agent.

## Markdown button

Most documentation pages display a **Markdown** button in the top-right area of the content, next to the page title. The button opens a menu with three options:

- **View page:** opens the Markdown version of the current page in a new tab
- **Copy content:** copies the full Markdown text to your clipboard
- **Copy link:** copies the `.md` URL to your clipboard

The button is available on content pages that have a Markdown equivalent and is the fastest way to grab Markdown for a specific page when browsing the documentation manually or pointing an AI assistant at a URL.

## Markdown index

Our site publishes [a machine-readable index](https://www.fastly.com/documentation/markdown-index.json) of all available Markdown pages at:

```plain
https://www.fastly.com/documentation/markdown-index.json
```

The index is a JSON file organized by content category (`guides`, `reference`, `solutions`, `developers`) with a flat `allPages` array for convenience. Each entry includes the page title, a short description, and the Markdown URL.

This index is useful for:

- Discovering what content is available without crawling the site
- Building search indexes or embeddings over the full documentation set
- Populating retrieval stores for LLM pipelines

## llms.txt

Our site publishes an [`llms.txt`](https://www.fastly.com/documentation/llms.txt) file. This is a curated plain-text index of the most important documentation pages, grouped by topic area:

```plain
https://www.fastly.com/documentation/llms.txt
```

The `llms.txt` file follows the [`llmstxt` specification](https://llmstxt.org) and provides a quick starting point for AI systems that need an overview of available content without processing the full index.