> For the complete documentation index, see [llms.txt](https://docs.apryse.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.apryse.com/explore-docs-with-ai/access-llms-full.txt.md).

# Access llms-full.txt

Give AI tools access to the full documentation in one file.

The `llms-full.txt` file contains the complete content of published documentation in a single, machine-readable format for AI assistants, agents, and development tools. While `llms.txt` helps AI tools find documentation resources, `llms-full.txt` provides the full documentation content as a comprehensive source of context.

### Discover the benefits

Using `llms-full.txt` helps to:

* Provide AI tools with complete documentation context from a single source.
* Reduce the need to locate and retrieve content from multiple pages.
* Improve the quality of documentation-based responses and interactions.
* Support AI-assisted development, troubleshooting, research, and code generation workflows.
* Expose documentation content in an AI-optimized format.
* Enable AI tools to reference information across documentation areas without relying on site navigation.

### Decide when to use

The `llms-full.txt` file is best when you want an AI tool to understand a large portion of the documentation rather than a single page.

| Use llms-full.txt to                                                                         | Consider another option to                                                                                                                               |
| -------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Give AI tools comprehensive documentation context from a single source.                      | <p>Ask questions while browsing documentation.<br>→ Use <a href="/explore-docs-with-ai/chat-with-ai-assistant.md">AI Assistant</a></p>                   |
| Ask questions that span multiple documentation areas.                                        | <p>Work with a specific documentation page in an AI tool.<br>→ Use <a href="/explore-docs-with-ai/access-docs-as-markdown.md">Markdown pages</a></p>     |
| Build AI-powered search or support experiences using the documentation.                      | <p>Help AI tools discover available documentation resources.<br>→ Use <a href="/explore-docs-with-ai/access-llms.txt.md">llms.txt</a></p>                |
| Use documentation as the primary knowledge source for an AI assistant.                       | <p>Connect AI tools directly to documentation through a standardized integration.<br>→ Use <a href="/explore-docs-with-ai/connect-to-mcp.md">MCP</a></p> |
| Generate examples, summaries, and recommendations from a broad set of documentation content. | <p>Access real-time documentation content through a direct integration.<br>→ Use <a href="/explore-docs-with-ai/connect-to-mcp.md">MCP</a></p>           |

### Access the llms-full.txt file

Most AI-capable tools that can retrieve web content can use the `llms-full.txt` URL as a documentation source. To access the Apryse `llms-full.txt`, follow these steps.

{% stepper %}
{% step %}
Navigate to <https://docs.apryse.com/llms-full.txt>.
{% endstep %}

{% step %}
Share the URL with an AI assistant or agent. For example:

{% code expandable="true" %}

```
Use this documentation as your reference: 
https://docs.apryse.com/llms-full.txt
Summarize the available authentication points.
```

{% endcode %}
{% endstep %}
{% endstepper %}

### Explore examples

From your AI assistant or coding agent, add the following prompts to get started.

{% prompt description="Learn about a feature" defaultExpanded="partial" %}

```markdown
Explain how I can extract text from scanned PDF documents using Apryse's OCR module. Use this documentation: https://docs.apryse.com/llms-full.txt.
```

{% endprompt %}

{% prompt description="Generate a code sample" defaultExpanded="partial" %}

```markdown
Using this documentation as a reference, create a .NET example that demonstrates how to enable Microsoft Office-to-PDF conversion using the Apryse Server SDK: https://docs.apryse.com/llms-full.txt.
```

{% endprompt %}

{% prompt description="Provide context for coding agents" defaultExpanded="partial" %}

```markdown
Use this documentation as the primary reference when generating code: https://docs.apryse.com/llms-full.txt.
```

{% endprompt %}

{% prompt description="Troubleshoot an issue" defaultExpanded="partial" %}

```markdown
Review this documentation and identify possible causes of the "Bad license key" error message: https://docs.apryse.com/llms-full.txt.
```

{% endprompt %}

### Next steps

Now that you understand how to use `llms-full.txt` endpoints, explore other ways to work with documentation and AI:

* [Chat with AI Assistant](/explore-docs-with-ai/chat-with-ai-assistant.md)
* [Access docs as Markdown](/explore-docs-with-ai/access-docs-as-markdown.md)
* [Access llms.txt](/explore-docs-with-ai/access-llms.txt.md)
* [Connect to MCP](/explore-docs-with-ai/connect-to-mcp.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.apryse.com/explore-docs-with-ai/access-llms-full.txt.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.