How to Use the ONES MCP in AutoGen

Q: How does the ONES AutoGen integration protect our project workflows?

Vinkius wraps all listworkflows queries in isolated, ephemeral sandboxes under our secure MCP architecture with strict token authentication. Your internal R&D processes and transition rules are never exposed to unauthorized external agents.

Deploy AutoGen agents that debate ticket priority and update ONES project tasks through collaborative consensus.

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Connect ONES MCP to AutoGen

Create your Vinkius account to connect ONES to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ONES with AutoGen

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Debate Ticket Priority in AutoGen Conversations

`update_task` is the tool your AutoGen agents execute once they reach a consensus on ticket priority. This collaborative review prevents single-agent errors and ensures ONES updates match actual team capacity.

Audit Task Creation via Multi-Agent Review

`create_task` initiates a structured draft that a separate quality assurance agent must review before submission via the MCP protocol. If the draft lacks critical details, the AutoGen agents debate and pass the ticket back and forth to refine the ONES description.

Coordinate Team Assignments Automatically

`list_members` pulls your active directory into the AutoGen conversation so agents can negotiate task assignments. This automated negotiation ensures ONES tickets are distributed fairly across the engineering team via AutoGen conversation.

Setup guide

Set up ONES 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 ONES 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="ONES_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent ONES 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 ONES. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Common questions about ONES MCP in AutoGen

Yes, they can share the tool list. A coordinator agent might call list_tasks to gather context, while a worker agent executes update_task based on the group's decisions.

The McpToolAdapter automatically translates the MCP server's tool schemas into the format AutoGen expects. This ensures your agents can call get_project without manual schema mapping.

Yes, you can connect using StreamableHttpServerParams. This allows your multi-agent system to interact with the platform securely over standard web protocols.

The conversation continues until the agents reach a consensus or hit their maximum round limit. No call to update_task is made until the executing agent receives approval from the reviewer agent.

Vinkius wraps all list_workflows queries in isolated, ephemeral sandboxes under our secure MCP architecture with strict token authentication. Your internal R&D processes and transition rules are never exposed to unauthorized external agents.

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