How to Use the Amazing Marvin MCP in AutoGen

Q: How do I configure Amazing Marvin with AutoGen?

Install the autogen-extmcp package. Retrieve the tools using mcpservertools with a StreamableHttpServerParams configuration pointing to your Vinkius URL.

Q: How do AutoGen agents update Amazing Marvin tasks?

They use the updatetask tool to modify titles, scheduled days, or completion states. The agents negotiate the new parameters in chat before executing the update.

Deploy AutoGen agents that debate priorities and manage your Amazing Marvin workload automatically.

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Create your Vinkius account to connect Amazing Marvin 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 Amazing Marvin with AutoGen

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Analyze Workloads with AutoGen Agents

Feeding your daily schedule into a chat room starts with the `get_today_items` tool. A planning agent reviews the list while a time-management agent critiques the feasibility of completing everything. Digging deeper requires the `get_children` tool to expose nested sub-categories. The agents argue over which project deserves immediate attention before reaching a consensus on the next step.

Build Amazing Marvin Structures via Consensus

Triggering `add_category` creates high-level organizational buckets after the agents agree on a taxonomy. They discuss the optimal way to group incoming work before committing the change. The `add_task` tool inserts specific action items with assigned dates. One agent proposes a deadline, another challenges it based on historical velocity, and the final agreed date gets pushed to the API.

Execute Time Management via MCP Server

Firing the `start_tracking` tool initiates the timer on a specific piece of work. An execution agent starts the clock, performs its designated external research, and then calls `stop_tracking` when finished. Closing the loop relies on the `mark_done` function. A reviewer agent inspects the final deliverable and only flips the task status to completed if it passes strict criteria.

Setup guide

Set up Amazing Marvin 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 Amazing Marvin 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="Amazing Marvin_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install the autogen-ext[mcp] package. Retrieve the tools using mcp_server_tools with a StreamableHttpServerParams configuration pointing to your Vinkius URL.

Yes. You pass the tool list to the AssistantAgent constructor. The agents share access to the same workspace and coordinate their API calls during the conversation.

They use the update_task tool to modify titles, scheduled days, or completion states. The agents negotiate the new parameters in chat before executing the update.

The Vinkius endpoint works perfectly with local scripts. The McpToolAdapter handles all schema conversions between the remote server and your local environment automatically.

Every connection runs in an isolated, ephemeral sandbox. Your private task details, category names, and time tracking logs never persist on Vinkius servers after the session ends.

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