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

# Navigating These Docs

> How to read these docs as a human, and how to feed them to an AI tool or agent.

These docs are built for two kinds of readers: people, and the AI tools people build with. This page
covers both.

<Note>
  **Two different MCP servers.** The **docs MCP** on this page (`docs.prava.space/mcp`) lets an AI
  *read these docs*. The **payments MCP** (`mcp.pay.prava.space/mcp`) lets an agent actually *pay*;
  see [Prava MCP](/mcp/overview).
</Note>

## Reading as a human

Start at the [home page](/) and pick the card that matches you. Each card opens a path you can read
top to bottom:

| You are             | Read in this order                                                                                                                                                                   |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Evaluating Prava    | [Use Cases](/use-cases) → [How Prava Works](/concepts/how-it-works) → [Compliance](/guides/compliance)                                                                               |
| Building an AI app  | [Choosing Your Integration](/choosing-your-integration) → [Quickstart](/quickstart) → [the tutorial](/guides/add-payments-to-your-ai-app) → [API Reference](/api-reference/overview) |
| Connecting an agent | [Prava MCP](/mcp/overview) or [Prava CLI](/prava-pay/overview), then that section's pages in order                                                                                   |
| An agent owner      | [Your Prava Pay Dashboard](/prava-pay/your-wallet). One page; no code.                                                                                                               |

Stuck on a term? The [Glossary](/concepts/glossary) maps every name across the API, CLI, and
dashboard. Stuck on anything else? [FAQ](/developer-faq).

## Reading as an AI tool or agent

Three ways, from lightest to deepest:

1. **Paste an index**: [`llms.txt`](https://docs.prava.space/llms.txt) (page index) or
   [`llms-full.txt`](https://docs.prava.space/llms-full.txt) (entire docs as one file) into any LLM.
2. **Per-page**: every page has a top-right AI menu (copy as Markdown, open in ChatGPT/Claude, view
   raw Markdown).
3. **Connect the docs MCP** (below): your coding agent gets a live "search the Prava docs" tool and
   answers from current pages instead of stale training data.

And when the agent should *act*, not only read: connect the
[payments MCP](/mcp/connect) too.

## Connect the docs MCP server

We host a standard **Model Context Protocol (MCP)** server for these docs. MCP is an open protocol, so
**any MCP-compatible AI tool** can connect to the same endpoint and gain a "search the Prava docs"
capability: Claude Code, Cursor, VS Code / Copilot, Windsurf, Cline, Continue, Goose, Zed, and others.

Add this to your client's MCP settings:

```json theme={null}
{
  "mcpServers": {
    "prava-docs": {
      "url": "https://docs.prava.space/mcp"
    }
  }
}
```

### Quick-add by tool

<CodeGroup>
  ```bash Claude Code theme={null}
  claude mcp add --transport http prava-docs https://docs.prava.space/mcp
  ```

  ```text Cursor / Windsurf / VS Code theme={null}
  MCP settings → "Add server" → paste the URL:
    https://docs.prava.space/mcp
  ```

  ```text Claude (web / desktop) theme={null}
  Settings → Connectors → "Add custom connector" →
    Name: Prava Docs
    URL:  https://docs.prava.space/mcp
  ```
</CodeGroup>

### Older / stdio-only clients

If a client only supports local (stdio) MCP servers, bridge to the hosted endpoint with `mcp-remote`:

```bash theme={null}
npx -y mcp-remote https://docs.prava.space/mcp
```

Once connected, ask your agent things like *"Using the Prava docs, how do I create a payment session?"*
and it will pull the answer straight from these pages.

## Feed the docs to any LLM (llms.txt)

Prefer to paste context into a model directly? These docs publish machine-readable indexes:

| File                                                                               | What it is                                                        |
| ---------------------------------------------------------------------------------- | ----------------------------------------------------------------- |
| [`https://docs.prava.space/llms.txt`](https://docs.prava.space/llms.txt)           | A concise index of every page; good for navigation.               |
| [`https://docs.prava.space/llms-full.txt`](https://docs.prava.space/llms-full.txt) | The full docs as one text file; paste it in for complete context. |

Drop either URL (or its contents) into ChatGPT, Claude, or any LLM to ground it in Prava's documentation.

## Per-page AI actions

Every page has an AI menu in the top-right:

* **Copy page**: copy the page as clean Markdown.
* **Open in ChatGPT / Claude**: start a chat pre-loaded with this page.
* **View as Markdown**: see the raw Markdown a model would read.

## Why this matters for Prava

Prava is built for AI agents. Making the docs first-class for the tools your developers already use
(Cursor, Claude Code, and others) means less guesswork, fewer hallucinated API calls, and a faster path
from "what's Prava?" to a working integration.