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

# LLM & agent access

> Read these docs by machine: MCP server, llms.txt, Markdown views, and a copy-paste migration prompt

Everything on this site is designed to be read by an LLM as easily as by a person. If you are wiring up a coding agent — or you *are* the coding agent — use the surfaces below instead of scraping HTML.

## MCP server

The docs run a hosted [MCP](https://modelcontextprotocol.io) server at:

```text theme={"system"}
https://docs.valarhq.ai/mcp
```

It exposes search and retrieval tools over the full published site. Connect it to your client:

<CodeGroup>
  ```bash Claude Code theme={"system"}
  claude mcp add --transport http valar-docs https://docs.valarhq.ai/mcp
  ```

  ```json Cursor (mcp.json) theme={"system"}
  {
    "mcpServers": {
      "valar-docs": {
        "url": "https://docs.valarhq.ai/mcp"
      }
    }
  }
  ```
</CodeGroup>

You can also use the contextual menu on any page (the button next to the page title) to connect the MCP server, copy the page as Markdown, or open the page in ChatGPT, Claude, or Cursor.

[Use the docs MCP server](/docs-mcp) for connection steps, pricing examples, and troubleshooting. [Pricing for agents](/pricing-for-agents) provides a compact public rate table that you can retrieve through MCP or read as Markdown, with no API key.

## llms.txt and Markdown views

* [`/llms.txt`](https://docs.valarhq.ai/llms.txt) — an index of every page, one URL per line, for agents that want to pick what to read.
* [`/llms-full.txt`](https://docs.valarhq.ai/llms-full.txt) — the entire documentation in one file, for one-shot context loading.
* **Any page as Markdown** — append `.md` to a page URL, e.g. [`/quickstart.md`](https://docs.valarhq.ai/quickstart.md).
* [`/openapi.json`](https://docs.valarhq.ai/openapi.json) — the machine-readable API specification behind the API reference tab.

## Migrate an app with one prompt

Valar speaks the OpenAI Responses and Chat Completions APIs, so migrating is a base-URL, key, and model-id change. Paste this into a coding agent pointed at your repo:

```text theme={"system"}
Migrate this project from OpenAI to Valar (https://docs.valarhq.ai).
- Change the OpenAI client base_url to https://api.valarhq.ai/v1 and read the key from VALAR_API_KEY.
- Replace OpenAI model ids with a Valar model from /models (e.g. moonshotai/Kimi-K2.7).
- Keep request and response shapes the same; flag any OpenAI-only params Valar doesn't support (see /support).
```

[Migrating to Valar](/migrate) walks through the same change by hand, with the full compatibility table.

## Route your coding agent through Valar

Reading the docs is one thing; the agent itself can run on Valar. [ValarCode](/valarcode/overview) connects Claude Code, Cursor, Codex, and other harnesses to Valar with one command and cuts coding-model spend by more than half:

```bash theme={"system"}
valar claude on
```

See [Set up ValarCode](/valarcode/setup).