How to Use the Clustdoc MCP in AutoGen

Debate and finalize onboarding tasks in AutoGen using Clustdoc tools as the basis for agent decisions.

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Create your Vinkius account to connect Clustdoc 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 Clustdoc with AutoGen

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Multi-agent negotiation with Clustdoc tools

Set up a security agent to check dossier status via `get_application_status_details` while an operations agent manages the workflow. They debate whether to proceed based on the data returned. This ensures that no onboarding process moves forward until both agents agree. You see the reasoning process play out in the chat logs until they reach a consensus.

Automate Clustdoc workflows through agent consensus

Use `list_onboarding_templates` to present options to your agents during a planning session. They challenge each other on which template best fits the client's profile. Once the agents agree, they trigger `launch_new_onboarding` together. This keeps your team overhead low while ensuring every application follows the right procedure.

Manage Clustdoc teams with AutoGen agents

Grant your agents access to `list_clustdoc_teams` so they can assign tasks based on current availability. You watch the agents negotiate who is responsible for a specific dossier. They verify member profiles with `get_my_clustdoc_profile` to confirm permissions before taking action. It turns your onboarding into a collaborative task managed by your own logic.

Setup guide

Set up Clustdoc 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 Clustdoc 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="Clustdoc_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Clustdoc 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="Clustdoc_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Clustdoc 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 Clustdoc. 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 Clustdoc MCP in AutoGen

Agents share the output of Clustdoc tools in their conversation. They evaluate the data from `list_client_dossiers` and debate the best next step for the client.

Yes, once you pass the tools to the AssistantAgent, the agents decide when to call functions like `send_onboarding_invitation` based on their internal debate.

The server uses encrypted transport for all communications. Only the specific dossier and user profile data requested by your agents enters the conversation stream.

You can use the streamable HTTP transport. This allows your agents to consume the Clustdoc tool definitions as soon as the server is reachable.

The agents report back if a tool call fails. You see the error message in the chat and can instruct the agents to retry or adjust their approach.

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