How to Use the Chuangkit / 创客贴 MCP in AutoGen

Q: Does this MCP Server support human-in-the-loop workflows with AutoGen?

Yes. You can configure a UserProxyAgent in AutoGen to prompt a human for input. For example, the agent team can propose a design found via searchtemplates and wait for your approval before proceeding.

Let your AutoGen agent teams debate and select the best Chuangkit designs for your project.

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Connect Chuangkit / 创客贴 MCP to AutoGen

Create your Vinkius account to connect Chuangkit / 创客贴 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.

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Setup Chuangkit / 创客贴 with AutoGen

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Enable Multi-Agent Design Reviews

Give your AutoGen agents the tools to have informed debates about design choices. A "Creative" agent can use `search_templates` to propose a few options for a new marketing campaign. Meanwhile, a "Brand" agent can use `get_template` on those suggestions to check if the fonts and color palettes are compliant. They discuss the trade-offs and arrive at a consensus, all logged in the conversation.

Automate Asset Audits with Your AutoGen Team

Set up a team of agents to audit your existing creative library. One agent uses `list_user_designs` to create a work queue. A second agent takes each design and runs `get_design_detail` to inspect its properties. A third "Auditor" agent can then flag designs that are off-brand or use outdated logos. This MCP Server gives your agents the ground truth they need to collaborate.

Brainstorm with a Chuangkit-Aware Agent

Use agents to explore the creative possibilities within Chuangkit. An agent can start by calling `list_categories` to understand the available design types. Based on the conversation, another agent can dive deeper, using `list_materials` to find specific stock photos or icons. It's a dynamic way for an agent team to assemble a mood board before starting a new design.

Setup guide

Set up Chuangkit / 创客贴 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 Chuangkit / 创客贴 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="Chuangkit / 创客贴_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Chuangkit / 创客贴 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="Chuangkit / 创客贴_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Chuangkit / 创客贴 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 Chuangkit / 创客贴. 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 Chuangkit / 创客贴 MCP in AutoGen

Assign the tools to different agents based on their roles. For example, a planner agent can use `list_categories`, while an executor agent uses `get_template` and `get_asset_url` to act on the planner's ideas.

Yes, that's a perfect use case for AutoGen. One agent calls `search_templates` to find options, and a second agent with different instructions calls `get_design_detail` to verify them, with the results discussed in their conversation.

You can provide the full list of tools from this MCP Server to an `AssistantAgent`. Then, through prompting, you instruct the agent on which persona should be responsible for calling specific tools like `search_templates`.

Yes. You can configure a `UserProxyAgent` in AutoGen to prompt a human for input. For example, the agent team can propose a design found via `search_templates` and wait for your approval before proceeding.

Your AutoGen agents will access Chuangkit template and design data to make decisions. The actual data transfer happens over a secure, token-based connection managed by Vinkius. The MCP Server itself is ephemeral and doesn't store your design content.

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