# Do you deliver data in an LLM-optimized format?

Yes, the Model Context Protocol (MCP) support is a built-in feature of our [Web Scraper API](https://oxylabs.io/products/scraper-api/web). The MCP process transforms raw HTML into formats that Claude, GPT, and other models can immediately understand. No manual reformatting is required.

{% hint style="info" %}
🛠️ MCP acts as a wrapper that structures the Web Scraper API’s output with context, metadata, and instructions, ensuring compatibility with LLMs.
{% endhint %}

Web Scraper API can also return [Markdown output](/products/web-scraper-api/features/result-processing-and-storage/output-types/markdown-output.md) by adding `"markdown": true` to your request. Markdown is a lightweight, LLM-friendly, and easy-to-read format that preserves structure and emphasis, making it ideal for chunking, metadata extraction, and preprocessing in AI workflows.

Alternatively, you can use [AI Studio](https://aistudio.oxylabs.io/) to scrape websites using natural language prompts. It can deliver content in Markdown format and parse data according to your prompt or a provided Pydantic or JSON schema.


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# Agent Instructions: 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:

```
GET https://developers.oxylabs.io/help-center/data-for-llms/do-you-deliver-data-in-an-llm-optimized-format.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.