Lanhu MCP Server for AutoGen 10 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Lanhu as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="lanhu_agent",
tools=tools,
system_message=(
"You help users with Lanhu. "
"10 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* 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 Lanhu MCP Server
Empower your AI agent to orchestrate your product design workflow with Lanhu (蓝湖), the premier design collaboration platform for high-performance teams. By connecting Lanhu to your agent, you transform complex design handoffs and project coordination into a natural conversation. Your agent can instantly list your projects, retrieve design file information, audit layer structures, and even browse team comments without you needing to navigate the web interface. Whether you are managing a mobile app design or a large-scale enterprise system, your agent acts as a real-time design coordinator, keeping your assets organized and your production moving.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Lanhu tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Project Orchestration — List all accessible design projects and files across your Lanhu workspace.
- Design Auditing — Retrieve detailed metadata about design files, including layers and node structures.
- Collaboration Monitoring — Browse file comments and discussions to stay informed about team feedback.
- Board Management — Access design boards to understand project organization and milestones.
- Team Coordination — List teams and members to manage assignments and participation effectively.
The Lanhu MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Lanhu to AutoGen via MCP
Follow these steps to integrate the Lanhu MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 10 tools from Lanhu automatically
Why Use AutoGen with the Lanhu MCP Server
AutoGen provides unique advantages when paired with Lanhu through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Lanhu tools to solve complex tasks
Role-based architecture lets you assign Lanhu tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Lanhu tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Lanhu tool responses in an isolated environment
Lanhu + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Lanhu MCP Server delivers measurable value.
Collaborative analysis: one agent queries Lanhu while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Lanhu, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Lanhu data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Lanhu responses in a sandboxed execution environment
Lanhu MCP Tools for AutoGen (10)
These 10 tools become available when you connect Lanhu to AutoGen via MCP:
get_board
Get board details
get_comments
Get file comments
get_file
Get design file info
get_project
Get project details
list_boards
List project boards
list_layers
List file layers
list_members
List team members
list_project_files
g., from Sketch, Figma, XD) within a specific project. List project design files
list_team_projects
List team projects
list_teams
List all Lanhu teams
Example Prompts for Lanhu in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Lanhu immediately.
"List all my design projects on Lanhu."
"Show me the comments for design file 'checkout-v1'."
"List the layers for file 'homepage-main'."
Troubleshooting Lanhu MCP Server with AutoGen
Common issues when connecting Lanhu to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Lanhu + AutoGen FAQ
Common questions about integrating Lanhu MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Lanhu with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Lanhu to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
