How to Use the Common Room MCP in AutoGen

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Connect Common Room MCP to AutoGen

Create your Vinkius account to connect Common Room 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 Common Room with AutoGen

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Perplexity

Debate segments using AutoGen agents

Let your agents argue over which members belong in a segment. One agent calls `list_segment_members` while another challenges the criteria. They negotiate until they reach a consensus. You get a final decision backed by live data from the server.

Audit Common Room activity with AutoGen

Assign a security agent to monitor `list_activity_types` for anomalies. If it finds something odd, it reports back to the lead agent for a final review. This multi-agent setup forces deliberation. You avoid impulsive actions by making the agents check each other's work.

Automate consensus with tool adapters

The McpToolAdapter automatically converts your API schema for the agents. They know exactly how to use `search_contacts` to resolve a conflict. They share the results in their conversation history. You watch the debate unfold in real-time as they converge on a result.

Setup guide

Set up Common Room 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 Common Room 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="Common Room_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Common Room MCP in AutoGen

Agents pass tool results back and forth through their conversation thread. If one agent finds a contact, the other agent uses that info to refine its own search.

Agents are explicitly designed to debate conclusions. If the data from `get_contact_tags` seems off, one agent will flag it for the other to investigate.

Yes, the adapter handles the tool schema automatically. You just plug the server into your agent constructor and the agents start talking.

Vinkius handles all auth via an endpoint token. Your agents never see your actual API credentials.

We process all data through an ephemeral V8 sandbox. Each interaction is isolated, ensuring that contact records are never exposed outside your specific agent session.

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