How to Use the Lunatask MCP in AutoGen

Debate your work priorities using AutoGen and the Lunatask MCP Server for multi-agent consensus.

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Connect Lunatask MCP to AutoGen

Create your Vinkius account to connect Lunatask 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 Lunatask with AutoGen

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Perplexity

Coordinate tasks with AutoGen agents

Set up a planning agent to read `list_tasks_metadata` and a execution agent to perform the work. They discuss the priority of each task before taking action. Once they agree, the execution agent calls `create_new_task`. You get a decision based on multiple perspectives rather than a single prompt.

Debate habit tracking in AutoGen

Your agents compare your habit goals against your current completion logs. One agent challenges the frequency while another checks the data via `track_habit_completion`. They reach a consensus on whether to adjust your schedule. This keeps your habits aligned with your actual performance.

Manage journals in AutoGen

Multiple agents analyze your note headers from `list_notes_metadata` to assess your project status. They debate which notes are outdated and need revision. After they reach an agreement, they use `create_journal_entry` to log the summary. You receive a consolidated view of your project health.

Setup guide

Set up Lunatask 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 Lunatask 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="Lunatask_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Lunatask 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 Lunatask. 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 Lunatask MCP in AutoGen

Use the MCP adapter to pass the tool list to your agents. They gain access to the server functions as part of their available toolkit.

Yes, the agents operate in a shared context. They can pass information retrieved from the server back and forth during their debate.

The server protects your data by providing only metadata. The agents never see the unencrypted content of your tasks or journals.

They might, but that is the point. You configure them to challenge each other, ensuring the final action is vetted by both agents.

The agent logs provide a clear view of which tool was called and why. You can review the debate history to see how the decision was reached.

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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