How to Use the HTML DOM Query Engine MCP in AutoGen

Enable multi-agent debate and extraction in AutoGen with the HTML DOM Query Engine MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect HTML DOM Query Engine MCP to AutoGen

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

GDPR Free for Subscribers

Setup HTML DOM Query Engine with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Agentic DOM extraction in AutoGen

Give your agents the ability to read web pages as part of their deliberation process. The `query_dom` tool provides a clear, JSON-formatted output that multiple agents can discuss and analyze simultaneously. This allows your team of agents to debate the veracity of web content. One agent can query the DOM, and another can critique the extracted data, ensuring the final decision is based on verified information.

Consensus-based scraping in AutoGen

Use the HTML DOM Query Engine to feed data into a multi-agent workflow where agents challenge each other's findings. By using `query_dom`, you ensure that the raw input is consistent, so debates focus on content rather than parsing errors. Your setup can include a dedicated 'scraper' agent that executes the tool and a 'validator' agent that checks if the extracted text meets specific criteria.

Native MCP support in AutoGen

Connect the MCP Server directly to your AssistantAgent instances. The McpToolAdapter automatically converts the `query_dom` schema, so your agents can invoke it as if it were a native Python function. This integration is lightweight. It supports standard transports, meaning you can keep your agents running locally while the MCP Server handles the heavy lifting of DOM traversal.

Setup guide

Set up HTML DOM Query Engine MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes HTML DOM Query Engine tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="HTML DOM Query Engine_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent HTML DOM Query Engine data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="HTML DOM Query Engine_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent HTML DOM Query Engine data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cheerio DOM. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect HTML DOM Query Engine now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about HTML DOM Query Engine MCP in AutoGen

Yes, you can register the tools list with any agent in your group chat. This allows every agent to invoke the HTML DOM Query Engine as needed during their collaborative problem-solving.

The extension package handles this automatically. It maps the server's tools to the expected format for your AutoGen agents without you needing to write manual wrappers.

Not at all. The parsing is highly optimized, ensuring that the agents get their data quickly so they can continue their discussion without unnecessary pauses.

It is. Whether you prefer HTTP or stdio, the server adapts to your AutoGen configuration, providing a flexible way for your agents to access external web data.

We use a zero-trust architecture. Every request to the HTML DOM Query Engine is authenticated via your endpoint token, and the ephemeral sandbox ensures that any HTML payloads processed by your agents are destroyed immediately after use.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript