How to Use the Yodiz MCP in AutoGen

Q: How do I get project context using Yodiz and AutoGen?

You start by providing the list of projects via listprojects. The agents then debate which projects are highest priority, forcing a consensus on the next steps for your workflow.

Q: Can I use Yodiz and AutoGen to validate user roles?

Yes. One agent calls listusers to gather all identifiers. A second agent can then challenge that list, debating if the current team structure is adequate for the tasks at hand.

Q: What’s the best way to manage requirements with Yodiz and AutoGen?

Use listuserstories within an agent conversation. The agents can debate which stories are most critical or if they need more detail, achieving a high degree of consensus on scope.

Q: Does the MCP Server handle complex project structures with Yodiz and AutoGen?

Absolutely. Agents can coordinate calls like listsprints followed by listbugs, debating whether the current sprint schedule is realistic given the number of open issues.

Get consensus on Yodiz features using AutoGen's multi-agent debate framework.

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Create your Vinkius account to connect Yodiz 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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Determining Project Scope

Don't just list projects; make agents discuss them. The first step is calling `list_projects` to give multiple agents a shared dataset of every Yodiz initiative. The agents can then debate which project needs the most attention or which one presents the highest risk, converging on a prioritized action plan.

Structuring Feature Requirements

When an agent calls `list_epics` and `list_user_stories`, they don't just get data—they argue over dependencies. The agents debate the feasibility of moving from a high-level epic to specific, actionable user stories. This consensus process ensures all required perspectives are considered before implementation.

Validating Team and Issues

The multi-agent setup is great for validation. One agent can call `list_users` to check team capacity, while another calls `list_bugs` to flag outstanding issues. The agents then challenge each other's findings: 'Are there enough users available to fix these critical bugs?'

Setup guide

Set up Yodiz 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 Yodiz 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="Yodiz_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Yodiz. 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 Yodiz MCP in AutoGen

You start by providing the list of projects via `list_projects`. The agents then debate which projects are highest priority, forcing a consensus on the next steps for your workflow.

Yes. One agent calls `list_users` to gather all identifiers. A second agent can then challenge that list, debating if the current team structure is adequate for the tasks at hand.

Use `list_user_stories` within an agent conversation. The agents can debate which stories are most critical or if they need more detail, achieving a high degree of consensus on scope.

Absolutely. Agents can coordinate calls like `list_sprints` followed by `list_bugs`, debating whether the current sprint schedule is realistic given the number of open issues.

This server touches user account information. Specifically, the `list_users` tool retrieves names and identifiers for all registered users in the workspace.

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