How to Use the HTML DOM Query Engine MCP in LlamaIndex

Q: How do I filter tools when using the HTML DOM Query Engine with LlamaIndex?

Use the allowedtools filter during your agent initialization. This keeps your LlamaIndex environment focused, ensuring the agent only uses the query tool for specific DOM operations.

Index live web data into LlamaIndex using the HTML DOM Query Engine MCP Server.

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Connect HTML DOM Query Engine MCP to LlamaIndex

Create your Vinkius account to connect HTML DOM Query Engine to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HTML DOM Query Engine with LlamaIndex

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Populate LlamaIndex with precise DOM extracts

Transform raw web content into queryable knowledge base entries. The `query_dom` tool allows you to isolate specific tags or class content before the indexer processes it, resulting in cleaner vector embeddings. This workflow prevents noise from entering your index. By filtering out navigation bars and footer clutter via CSS selectors, your RAG system performs better on specific data retrieval tasks.

Efficient indexing for LlamaIndex

Parse large HTML files without overwhelming your local system memory. The `query_dom` tool processes streams effectively, making it ideal for bulk indexing jobs where you need to scrape hundreds of pages. LlamaIndex agents can now trigger extraction on demand. When a user asks a question, the agent calls the tool, grabs the latest data, and updates the index in real-time.

Grounded responses in LlamaIndex

Eliminate hallucinations by ensuring your agent reads live data through the MCP Server. When you map `query_dom` output to your FunctionAgent, the model answers based on the current page structure rather than stale training data. This keeps your knowledge base current. Every time the agent runs, it pulls fresh attributes and text to verify its understanding of the target site.

Setup guide

Set up HTML DOM Query Engine MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all HTML DOM Query Engine MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to HTML DOM Query Engine tools.",
)
response = await agent.run("List recent HTML DOM Query Engine data")

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Common questions about HTML DOM Query Engine MCP in LlamaIndex

Yes, you can integrate it as a standard tool spec. By adding the HTML DOM Query Engine to your LlamaIndex setup, you can immediately start extracting and indexing data directly into your vector store.

Use the allowed_tools filter during your agent initialization. This keeps your LlamaIndex environment focused, ensuring the agent only uses the query tool for specific DOM operations.

The underlying engine is designed to be forgiving with standard markup. Even if the HTML structure is slightly off, the CSS selector logic usually finds the target elements without issue.

It is built for speed. Most extractions complete in under 50ms, meaning your LlamaIndex agent won't hang while waiting for the server to parse the DOM.

The server operates in an ephemeral Vinkius sandbox that wipes your data as soon as the tool call completes. No traces of your raw HTML payloads or extracted attributes are persisted on our infrastructure.

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