How to Use the Atlas MCP in AutoGen

Debate support strategies by connecting Atlas to AutoGen multi-agent systems.

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Connect Atlas MCP to AutoGen

Create your Vinkius account to connect Atlas 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 Atlas with AutoGen

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Perplexity

Debating support issues in AutoGen

One agent calls `get_ticket` while another critiques the proposed response. They negotiate the best way to handle the request. This stops bad data from reaching a customer. The agents challenge each other until they reach a consensus.

Managing team users with AutoGen

Your system uses `list_users` to see which agents are active. It then assigns the ticket to the right person based on current workload. The agents handle the delegation logic. You just watch the conversation unfold in the terminal.

Schema conversion for AutoGen

The McpToolAdapter maps Atlas definitions to your agent requirements automatically. You don't have to write custom wrappers for `get_account_check`. Everything works out of the box. You spend your time building the conversation logic instead of wiring up endpoints.

Setup guide

Set up Atlas 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 Atlas 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="Atlas_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Atlas MCP in AutoGen

Install the extension package and pass the server URL to the mcp_server_tools helper. Your AssistantAgent will then have access to all eight tools.

That is the point of the framework. You can set up a security agent to flag sensitive ticket info while a support agent drafts the reply.

We use isolated ephemeral containers for every request. Your session tokens are handled securely by the Vinkius gateway.

No. The system remains stateless. Your support data exists only within the memory of your active agents during the conversation.

You can monitor the conversation history to see where the logic went wrong. The agents keep a record of every tool call they make.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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