How to Use the MPU-Manager MCP in AutoGen

Q: How do I load MPU-Manager tools into AutoGen?

Install autogen-extmcp and use mcpservertools with your HTTP endpoint. Pass the resulting tool list directly into your AssistantAgent constructor.

Q: Can AutoGen agents collaborate on MPU-Manager cases?

Yes. One agent can call listcases to find open projects, while another uses getcase to analyze the specifics. They share the context in their conversation thread.

Q: Do I need to format the MPU-Manager schemas manually for AutoGen?

No. The McpToolAdapter automatically translates the server's JSON schema into a format the Microsoft framework understands. Your agents know exactly what arguments to pass.

Let your AutoGen agents debate and coordinate broadcast schedules using MPU-Manager.

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Connect MPU-Manager MCP to AutoGen

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Setup MPU-Manager with AutoGen

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Multi-Agent Schedule Coordination

Tools like `list_appointments` and `create_appointment` allow competing AutoGen agents to negotiate crew assignments. A producer agent proposes a time slot, while a logistics agent checks the calendar for conflicts. They argue until they find a window that works for both the camera crew and the director. Once consensus is reached, the logistics agent executes the booking.

Autonomous Production Planning

Executing `get_client` and `create_case` lets your agents draft and approve new production records without human oversight. The research agent pulls the client history, and the planning agent structures the new case. If the planning agent misses a required field, the validation agent rejects the proposal. They iterate on the data structure until the payload is perfect before writing to the database.

MPU-Manager MCP Server Health Checks

Calling `check_mpumanager_status` gives your system administrator agent the ability to verify database uptime. If the ping fails, the agent alerts the team instead of letting the other agents spam broken requests. Your reporting agents rely on this check before they pull data with `list_reports`. You avoid cascading failures in your multi-agent conversations by establishing a clear chain of command for infrastructure health.

Setup guide

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

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

    result = await agent.run("List recent MPU-Manager 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 MPU-Manager. 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 MPU-Manager MCP in AutoGen

Install `autogen-ext[mcp]` and use `mcp_server_tools` with your HTTP endpoint. Pass the resulting tool list directly into your `AssistantAgent` constructor.

Yes. One agent can call `list_cases` to find open projects, while another uses `get_case` to analyze the specifics. They share the context in their conversation thread.

No. The `McpToolAdapter` automatically translates the server's JSON schema into a format the Microsoft framework understands. Your agents know exactly what arguments to pass.

You assign specific tools to specific agents. Give the scheduler agent access to `create_appointment`, and restrict the reporting agent to `list_reports`.

Only the agents you authorize to read the schedule. Authentication requires a single endpoint token, and the managed MCP infrastructure ensures external actors cannot intercept your crew management API calls.

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