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

# AI integration

> Use the built-in AI assistant, load the docs into your AI editor, or connect any LLM directly to the BMONI Embedded documentation.

BMONI Embedded docs ship with several AI integrations out of the box. You can chat with the docs, open any page directly in your AI editor, or point an MCP-compatible agent at the full documentation corpus.

***

## Built-in AI assistant

Click the **Ask AI** button in the top-right of any page to open the Mintlify assistant. It is trained on all BMONI Embedded documentation — SDK, UI Kit, Wallets & Cards, and the API reference — and can answer questions, generate integration code, and walk you through setup flows.

<Info>
  The assistant is always up-to-date with the latest published docs. No extra configuration is needed.
</Info>

***

## Open any page in your AI editor

Every page has a contextual toolbar (bottom-right of each code block) with one-click actions for:

<CardGroup cols={3}>
  <Card title="Cursor" icon="arrow-up-right-from-square">
    Opens the page in Cursor's AI chat with full context pre-loaded.
  </Card>

  <Card title="Claude" icon="arrow-up-right-from-square">
    Opens the page in Claude.ai as a new conversation.
  </Card>

  <Card title="ChatGPT" icon="arrow-up-right-from-square">
    Opens the page in ChatGPT with the content pre-filled.
  </Card>

  <Card title="Windsurf" icon="arrow-up-right-from-square">
    Opens in Windsurf IDE with context injected.
  </Card>

  <Card title="Google AI Studio" icon="arrow-up-right-from-square">
    Opens the page in AI Studio.
  </Card>

  <Card title="Perplexity" icon="arrow-up-right-from-square">
    Opens as a Perplexity research query.
  </Card>
</CardGroup>

***

## MCP — connect any AI agent to the docs

Mintlify exposes the full documentation corpus as an **MCP (Model Context Protocol) server**. Any MCP-compatible agent — Claude Desktop, Cursor, Windsurf, Devin — can query the docs as a tool.

### Add to Claude Desktop

<Steps>
  <Step title="Open Claude Desktop settings">
    Go to **Settings → Developer → Edit Config** (`claude_desktop_config.json`).
  </Step>

  <Step title="Add the BMONI docs MCP server">
    ```json claude_desktop_config.json theme={null}
    {
      "mcpServers": {
        "bmoni-embedded-docs": {
          "command": "npx",
          "args": [
            "-y",
            "@mintlify/mcp@latest",
            "--docs-url",
            "https://embedded-dev.bmoni.com/docs"
          ]
        }
      }
    }
    ```
  </Step>

  <Step title="Restart Claude Desktop">
    Quit and reopen Claude Desktop. The `bmoni-embedded-docs` tool will appear in the tool list.
  </Step>

  <Step title="Start asking">
    Ask Claude anything about the SDK, UI Kit, or wallet cards — it can now retrieve exact content from the docs.

    > *"Show me how to provision a wallet with bmoni\_embedded\_sdk and gate signing with a PIN."*
  </Step>
</Steps>

### Add to Cursor

Open **Cursor Settings → MCP** and add:

```json theme={null}
{
  "bmoni-embedded-docs": {
    "command": "npx",
    "args": [
      "-y",
      "@mintlify/mcp@latest",
      "--docs-url",
      "https://embedded-dev.bmoni.com/docs"
    ]
  }
}
```

Cursor's AI will now retrieve BMONI documentation when you ask about the SDK, UI Kit, or wallet card components.

***

## llms.txt — raw documentation index for LLMs

Mintlify auto-generates two plain-text files that any LLM can fetch directly:

| URL              | Contents                                                                |
| ---------------- | ----------------------------------------------------------------------- |
| `/llms.txt`      | Page titles and URLs — a lightweight index for agents to locate content |
| `/llms-full.txt` | Full page content for every page — paste into any LLM context window    |

```bash theme={null}
# Fetch the lightweight index
curl https://embedded-dev.bmoni.com/llms.txt

# Fetch the full content dump
curl https://embedded-dev.bmoni.com/llms-full.txt
```

### Use in a system prompt

If you are building an app that wraps an LLM, you can include the full docs as context:

```typescript theme={null}
const docsContent = await fetch(
  'https://embedded-dev.bmoni.com/llms-full.txt'
).then(r => r.text());

const response = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    {
      role: 'system',
      content: `You are a BMONI Embedded integration assistant. Here is the full documentation:\n\n${docsContent}`
    },
    { role: 'user', content: userQuestion }
  ]
});
```

***

## Quick-copy for AI prompts

Every code block in the docs has a **Copy** button and an **Ask AI** shortcut. For setup questions, the most effective prompt is:

```
Using the bmoni_embedded_sdk Flutter package, I need to:
1. Provision an on-device Ethereum wallet
2. Gate signing with a 6-digit PIN
3. Sign an EIP-191 message and return the signature

Show me the full Dart implementation.
```

Paste this into any of the AI editors above — the contextual toolbar pre-fills the relevant page content automatically.