How to Use the Infinity Work Manager MCP in AutoGen

Coordinate multi-agent debates on project tasks using the Infinity Work Manager MCP Server and AutoGen.

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Connect Infinity Work Manager MCP to AutoGen

Create your Vinkius account to connect Infinity Work Manager 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 Work Manager with AutoGen

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Perplexity

Consensus-based task management

Assign an agent to call `list_items` while another analyzes the results. They debate the priority of tasks before one agent executes `update_item`. Use this to avoid rash changes to project boards. Agents challenge each other's reasoning if a proposed update conflicts with existing item attributes.

Automated schema conversion for AutoGen

The McpToolAdapter automatically maps the 15 Infinity tools to the AutoGen agent format. You do not need to write manual wrappers for API calls. Focus on defining agent roles and conversation flows. The server handles the underlying JSON-RPC communication required for tool execution.

Safe board manipulation via agent debate

Require a security agent to approve any `delete_item` call before it runs. This prevents accidental data loss during automated cleanups. Log the full conversation history to audit why specific changes were made to your boards. You can trace back every `create_comment` to the agent that suggested it.

Setup guide

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

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

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

Get your connection token →

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Common questions about Infinity Work Manager MCP in AutoGen

Yes. Agents operate within a shared conversation context. One agent can fetch data, and the next can act on it based on the previous output.

Install the autogen-ext MCP package. Initialize the server connection and pass the tool list into your AssistantAgent constructor.

The McpToolAdapter performs the conversion automatically. It ensures your agents understand the required arguments for tools like `create_board`.

The agents continue debating until they reach a consensus. You can define a critic agent to force a resolution if they hit a stalemate.

All requests are authenticated via your token. Because the server runs in a local sandbox, only your authorized agents can trigger actions on your boards.

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