How to Use the Cloopen / 容联云 MCP in AutoGen

Q: How do I load Cloopen / 容联云 tools into AutoGen via MCP?

Install autogen-extmcp. Use mcpservertools with StreamableHttpServerParams pointing to your Vinkius URL. Pass the resulting tool list directly into your AssistantAgent.

Let AutoGen agents debate your telecom strategy using this dedicated MCP server. Deploy multi-agent systems that negotiate SMS sending and voice routing.

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Connect Cloopen / 容联云 MCP to AutoGen

Create your Vinkius account to connect Cloopen / 容联云 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 Cloopen / 容联云 with AutoGen

Ask AI about this MCP

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Perplexity

Multi-Agent Cloopen MCP Server Logic

Mass texting campaigns trigger strict carrier blocks. You need oversight before hitting the send button on thousands of notifications. A marketing agent drafts the message and suggests calling `send_sms`. A compliance agent blocks the action until it runs `list_templates` to verify the copy matches an approved format, ensuring delivery.

Debate Voice vs Text

Deciding between an SMS or a voice call depends on cost and urgency. Hardcoding these rules breaks when API pricing changes or networks go down. Your AutoGen setup pits a budget agent against a reliability agent. If `query_sms` shows a delivery failure, they negotiate whether to trigger `list_voice_codes` or retry the text based on the current account balance from `get_account_info`.

Audit Call Paths Collaboratively

Changing a live IVR menu risks dropping customer calls. Single-agent systems might approve a broken routing path blindly without testing edge cases. One agent fetches the current setup using `get_ivr` and proposes changes. A separate QA agent critiques the new flow, verifying that `list_callback` endpoints won't trap the caller in a loop.

Setup guide

Set up Cloopen / 容联云 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 Cloopen / 容联云 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="Cloopen / 容联云_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Cloopen / 容联云 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="Cloopen / 容联云_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Cloopen / 容联云 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 Cloopen / 容联云. 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 Cloopen / 容联云 MCP in AutoGen

Install `autogen-ext[mcp]`. Use `mcp_server_tools` with `StreamableHttpServerParams` pointing to your Vinkius URL. Pass the resulting tool list directly into your AssistantAgent.

Yes. The framework maps the MCP tool adapter across your entire multi-agent chat. Any authorized agent can trigger `get_app` or `send_sms` during the conversation.

An operator agent decides to connect two users. It proposes the action to a supervisor agent, which approves the parameters before finally executing `list_callback`.

You set the system prompt to require verification. The sending agent will fire `query_sms` after texting, and report the status back to the group chat for further action.

Nobody outside your immediate session. Vinkius handles the authentication securely, and the ephemeral sandbox drops all `get_ivr` data the second the tool finishes executing.

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