How to Use the Infinity MCP in AutoGen

Enable debate-driven project management in AutoGen by connecting the Infinity MCP Server to your multi-agent team.

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Connect Infinity MCP to AutoGen

Create your Vinkius account to connect Infinity 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 Infinity with AutoGen

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Coordinate agents with Infinity in AutoGen

Give your agents access to `update_board_item` so they can negotiate task status changes. They check the board, debate the priority, and update the task accordingly. This forces your agents to reach a consensus before modifying your project state. It prevents conflicting updates from happening automatically.

Verify connectivity with MCP Server tools

Run `check_api_health` before any agent starts a task to ensure the connection is stable. If the API is down, the agents can pause their negotiation. This adds a layer of reliability to your multi-agent system. It prevents the agents from making decisions based on stale or missing data.

Audit project status using AutoGen

Use `list_board_webhooks` to let your agents monitor changes in real-time. They can discuss new webhooks and decide if an action is required. This makes your agents reactive to your project environment. They stay informed about what is changing without you needing to intervene.

Setup guide

Set up Infinity 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 Infinity 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="Infinity_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Infinity MCP in AutoGen

Yes. Multiple agents can debate the best way to update a task and use the server tools to execute the final decision.

By providing a shared interface, agents can read the same board state. They then use this data to challenge each other's conclusions until they agree.

You can. The server maps its tools directly to the agent's capability list. This allows the agents to read and write to your boards as part of their conversation.

The tool adapter converts the API output into a format the agents understand. They then process this content as part of their debate.

The server requires your specific credentials for every session. Your data stays within the secure sandbox, and only authorized agents can trigger tool calls.

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