How to Use the Lanhu MCP in AutoGen

Q: Can Lanhu and AutoGen handle conflicting design feedback?

Yes. You can assign one agent to gather getcomments data and another to resolve conflicts, ensuring only agreed-upon changes reach your developers.

Debate design implementation with the Lanhu MCP Server and AutoGen agents.

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Negotiate design handoffs via agents

Set up a team of agents to reconcile design files. One agent calls `list_layers` to identify new UI elements, while another agent critiques the implementation plan using `get_file`. They debate the best approach to code these components. This consensus-driven process ensures that design constraints are respected before a single line of code is written.

Verify project requirements in real-time

Let your agents cross-reference project scope. One agent uses `get_project` to fetch current specifications, and another agent checks those against the actual boards pulled via `list_boards`. They catch discrepancies early. If a designer changes a board structure, the agents negotiate how to update the project plan, saving you from manual reconciliation.

Collaborate on design feedback

Use agents to synthesize team feedback. An agent retrieves comments via `get_comments` and presents them to a senior agent for prioritization. This filters the noise. The system gives you a summarized task list based on actual feedback, allowing you to focus on the high-priority design changes.

Setup guide

Set up Lanhu 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 Lanhu 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="Lanhu_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Lanhu data")
print(result.messages[-1].content)

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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="Lanhu_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Lanhu 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 Lanhu. 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.

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Common questions about Lanhu MCP in AutoGen

The tools are passed to the agent group. Individual agents can then invoke them as part of their deliberation process to gather design data.

Yes. You can assign one agent to gather `get_comments` data and another to resolve conflicts, ensuring only agreed-upon changes reach your developers.

It does. Because the server provides a stable tool set, agents can repeatedly call `get_board` or `list_layers` to verify facts during their discussion.

The connection is ephemeral and encrypted. Your design data is only accessed by the agents you explicitly authorize during the conversation.

It touches project metadata, board structures, and comment text. This is strictly read-only access to prevent unauthorized changes to your design files.

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