How to Use the AutoGen MCP in AutoGen

Connect native AutoGen agents to the MCP server for consensus-driven multi-agent decision making.

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Connect AutoGen MCP to AutoGen

Create your Vinkius account to connect AutoGen 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 AutoGen with AutoGen

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Orchestrate agents with AutoGen

Launch specialized agents that talk to each other to solve problems. Use `create_agent` to define their roles and constraints. Your agents will debate and challenge each other until they reach a decision. This server provides the infrastructure for their communication.

Run multi-agent workflows

Execute predefined workflows using `list_workflows` to see what is already configured. You pick the flow, and the agents handle the rest. This keeps your AutoGen setup clean and repeatable. You spend less time coding logic and more time observing the debate.

Inspect model availability

Run `list_models` to see which LLMs are configured for your agents. You switch between models to see which one performs better in a debate. This gives you direct control over the reasoning engine. You verify which models are ready for your specific AutoGen task.

Setup guide

Set up AutoGen 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 AutoGen 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="AutoGen_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about AutoGen MCP in AutoGen

You use the AssistantAgent constructor to pull in the tools provided by the server. The adapter handles the schema conversion automatically for your agents.

You can, by passing the tools list directly into the agent. This allows your agents to trigger session management or workflow tools as needed.

Sessions are managed by the server, so they remain available as long as the session ID exists. You call `list_sessions` to resume your work.

Logs are kept in the ephemeral sandbox provided by Vinkius. They are only accessible through your authenticated endpoint.

Your session conversations are protected by zero-trust standards. We isolate your data from other users and ensure only your token can access the logs.

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