HTML DOM Query Engine MCP Server for LlamaIndexGive LlamaIndex instant access to 1 tools to Query Dom

Name: HTML DOM Query Engine
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add HTML DOM Query Engine as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The HTML DOM Query Engine MCP Server for LlamaIndex is a standout in the Loved By Devs category — giving your AI agent 1 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to HTML DOM Query Engine. "
            "You have 1 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in HTML DOM Query Engine?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About HTML DOM Query Engine MCP Server

If an AI agent needs to scrape a product price from a 20,000-line e-commerce HTML page, passing the entire raw HTML to the LLM destroys its token limit and leads to hallucination. This MCP allows the LLM to pass the raw string and a CSS selector, instantly returning just the target data.

LlamaIndex agents combine HTML DOM Query Engine tool responses with indexed documents for comprehensive, grounded answers. Connect 1 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

The Superpowers

Token Saver: Offloads heavy DOM parsing to the native V8 runtime via Cheerio.
Precision Scraping: Supports complex CSS selectors (e.g. #main .price) and extracts specific attributes like href or src.

The HTML DOM Query Engine MCP Server exposes 1 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 HTML DOM Query Engine tools available for LlamaIndex

When LlamaIndex connects to HTML DOM Query Engine through Vinkius, your AI agent gets direct access to every tool listed below — spanning html-parsing, css-selectors, data-extraction, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

query

Query dom on HTML DOM Query Engine

Pass the HTML string and a CSS query (e.g. "h1", ".price", "#title"). Returns the matched text content or attributes. Parses a raw HTML string and extracts text or attributes using a CSS selector deterministically

Connect HTML DOM Query Engine to LlamaIndex via MCP

Follow these steps to wire HTML DOM Query Engine into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 1 tools from HTML DOM Query Engine

Why Use LlamaIndex with the HTML DOM Query Engine MCP Server

LlamaIndex provides unique advantages when paired with HTML DOM Query Engine through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine HTML DOM Query Engine tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain HTML DOM Query Engine tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query HTML DOM Query Engine, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what HTML DOM Query Engine tools were called, what data was returned, and how it influenced the final answer

HTML DOM Query Engine + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the HTML DOM Query Engine MCP Server delivers measurable value.

Hybrid search: combine HTML DOM Query Engine real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query HTML DOM Query Engine to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying HTML DOM Query Engine for fresh data

Analytical workflows: chain HTML DOM Query Engine queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for HTML DOM Query Engine in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with HTML DOM Query Engine immediately.

"Extract the text from `.product-price` from this 5,000 line HTML file."

"Extract all image source URLs (`src`) from the `.gallery img` selector."

"Get the text inside the `<h1>` tag."

Troubleshooting HTML DOM Query Engine MCP Server with LlamaIndex

Common issues when connecting HTML DOM Query Engine to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

HTML DOM Query Engine + LlamaIndex FAQ

Common questions about integrating HTML DOM Query Engine MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query HTML DOM Query Engine tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.