> ## Documentation Index
> Fetch the complete documentation index at: https://runmirrors.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Use these docs with AI

> Every page as raw markdown, an llms.txt index, and one-click handoff to your AI tools.

These docs are built to be read by AI assistants and agents as much as by people. If you're pointing a model at Mirrors (or you *are* the model), here's the fast path.

## Raw markdown for every page

Append `.md` to any docs URL to get the page as clean markdown, no HTML or chrome:

```text theme={null}
https://www.runmirrors.com/docs/quickstart.md
https://www.runmirrors.com/docs/api-reference/envs.md
```

## The index: llms.txt

One file lists every page with its description. Fetch it first to decide what to read:

```text theme={null}
https://www.runmirrors.com/docs/llms.txt
```

There's also a product-level overview at [`/llms.txt`](https://www.runmirrors.com/llms.txt) (positioning, pricing, key facts), and `llms-full.txt` bundles the entire docs into a single file if your tool prefers one fetch.

## One-click handoff

Every page has a contextual menu in the top-right corner:

* **Copy page**: the page as markdown, straight to your clipboard.
* **View as Markdown**: the raw `.md` twin.
* **Open in ChatGPT / Claude**: starts a chat with the page already loaded as context.
* **Open in Cursor / VS Code**: pulls the page into your editor's AI chat.

You can also ask questions right here: the docs' built-in assistant answers from this documentation and links its sources.

## Drive the product itself over MCP

Mirrors is also *operable* by agents, not only readable. The hosted [MCP server](/docs/mcp-server) exposes the full product surface (build, explore, query, and eval environments), so an assistant that has read these docs can do the work too:

```text theme={null}
https://api.runmirrors.com/mcp
```

<Tip>
  A good first prompt for an agent: "Fetch [https://www.runmirrors.com/docs/llms.txt](https://www.runmirrors.com/docs/llms.txt), read the pages relevant to my task, then connect to the Mirrors MCP server and do it."
</Tip>