# HTML DOM Query Engine MCP for AI Agents AI Agent Connect

> HTML DOM Query Engine lets you pull specific data out of massive HTML files using CSS selectors. It handles the heavy lifting of parsing so your agent doesn't choke on huge pages or waste tokens on junk data. Instead of feeding a whole site into your agent's context, you can target the exact elements you need, like prices, links, or headers, instantly and efficiently.

## Overview
- **Category:** loved-by-devs
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_yforvmpWi3y9TqnYhrCHzOXtUdI6qMtPsOkV6gLr/ai-agent-connect
- **Tags:** html-parsing, css-selectors, data-extraction, web-automation, dom-manipulation

## Description

If you've ever tried to scrape a massive e-commerce page, you know the pain of hitting token limits. Passing a 20,000-line HTML file to your agent is a quick way to get hallucinations or just a 'context window full' error. This Connector solves that by letting your agent act like a scalpel. Instead of the agent trying to digest the whole page, it just hands the raw HTML and a CSS selector to the tool. The tool does the heavy lifting of parsing the DOM in the background and returns only the specific data you actually want, like a price or a source link. It's a way to keep your context window clean and your agent focused on the actual task. It's one of the most practical tools in the Vinkius catalog for anyone who needs to move past the copy-paste phase of web scraping and start doing something useful with the results. It allows you to target specific elements like headers, prices, or image sources without all the extra junk. You don't have to worry about the agent getting lost in a sea of scripts, styles, or navigation menus. This tool keeps the data clean and the workflow fast. It's the difference between your agent struggling to read a whole book versus just looking at the specific line you asked for. You get the data you need, exactly when you need it, without the overhead of processing the parts of the page that don't matter.

## Tools

### query_dom
Pass a raw HTML string and a CSS selector to get specific text or attributes. It handles the parsing so your agent stays focused on the data.

## Prompt Examples

**Prompt:** 
```
Look at this HTML and get the price.
```

**Response:** 
```
✅ **Matches Found:**
1. `$149.99`
```

**Prompt:** 
```
Get all images from the gallery.
```

**Response:** 
```
✅ **Matches:** Extracted 12 `src` attributes successfully.
```

**Prompt:** 
```
What's the main title?
```

**Response:** 
```
✅ **Matched Text:** 'Welcome to our API documentation.'
```

## Capabilities

### Extract text from specific elements
Pull only the text from tags like headers, paragraphs, or divs using CSS selectors.

### Grab attributes like source URLs
Extract specific values like image sources or link destinations directly from the DOM.

### Filter out unnecessary HTML tags
Strip away scripts, styles, and other noise to keep your agent's context clean.

### Handle massive page payloads
Process huge HTML files that would otherwise exceed your agent's token limits.

### Execute precise CSS selector queries
Use complex selectors to target exact elements regardless of how messy the source code is.

## Use Cases

### E-commerce Price Tracking
An agent scrapes a product page, pulls the price using a CSS selector, and logs it to a sheet without reading the whole site code.

### Gallery Scraping
You need all image links from a site; the agent uses a selector to grab every source attribute instantly.

### Documentation Parsing
Extracting specific code blocks from a huge documentation page without reading the whole site.

### Menu Navigation
Grabbing all anchor tags from a navigation bar to map out a site's structure.

## Benefits

- Save on costs by only sending the relevant data to your agent instead of the entire HTML payload.
- Stop hallucinations by giving your agent clean, specific text instead of a messy 20,000-line page.
- Use complex CSS selectors like #main .price to target exactly what you need every time.
- Pull specific attributes like src or href directly into your workflow using query_dom.
- Handle massive files that would normally crash a standard LLM context window.

## How It Works

The bottom line is your agent gets the exact data it needs without wasting a single token on irrelevant HTML.

1. Provide the raw HTML string and a CSS selector to the agent.
2. The Connector parses the string using the native V8 runtime.
3. You get back the specific text or attribute values you need.

## Frequently Asked Questions

**How does HTML DOM Query Engine help with web scraping?**
It lets your agent grab specific data points like prices or links from huge pages without having to read the whole file. This keeps your agent focused and prevents it from getting overwhelmed by unnecessary code.

**Can it handle very large HTML files?**
Yes, it handles massive HTML payloads by parsing them in the background. This means you can process pages with thousands of lines of code without hitting token limits or crashing your agent.

**Does it work with complex CSS selectors?**
It works with any standard CSS selector. You can use IDs, classes, and nested selectors to pinpoint exactly which piece of information you need to extract.

**How does this save on AI costs?**
It saves money by significantly reducing the amount of text sent to the AI. Since you only send the final extracted data instead of a whole webpage, you use fewer tokens for every request.

**Can I extract attributes like image sources?**
Yes, it can pull specific attributes like src or href from any element. This is useful for gathering image galleries or mapping out links on a website.

**Does it download the URL?**
No, it parses raw HTML strings that you pass to it.

**Can it extract link URLs?**
Yes, just pass 'href' in the attribute parameter.

**Is it fast?**
Yes, it uses Cheerio, which runs entirely in memory without a headless browser.