How to Use the Armano MCP in AutoGen

Q: How do I register Armano MCP Server tools in an AutoGen workflow?

Install autogen-extmcp and use mcpservertools with StreamableHttpServerParams pointing to your Vinkius endpoint. Pass the resulting tools list directly to your AssistantAgent constructor.

Q: Can AutoGen agents create new time entries in Armano?

Yes, you assign the createtimeentry tool to a specific agent in your group chat. That agent executes the tool once the other agents agree that the logged hours are valid.

Q: How do AutoGen agents share Armano project details during a debate?

Agents share the output of getproject by posting it to the group chat. The other agents read this message, parse the project details, and use that context for their next reasoning step.

Deploy AutoGen agents to debate and audit Armano timesheets, projects, and employee allocations automatically.

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Setup Armano with AutoGen

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Audit Armano MCP Server data via AutoGen debate

AutoGen lets you set up specialized agents that discuss Armano data retrieved via `list_projects` before taking action. For example, a PM agent checks timelines while a finance agent checks `list_time_entries` to negotiate budget allocations. The agents converse until they reach a consensus. If an employee's logged hours exceed the project limit, the agents debate the discrepancy using data from `get_time_entry` before flagging it for human review.

Automate leave approval workflows

You build an approval loop where one agent pulls pending requests using `list_leaves` and another checks team capacity. They collaborate to determine if the leave impacts active deliverables. This multi-agent deliberation prevents scheduling bottlenecks. By combining outputs from `list_departments` and individual schedules, the agents arrive at a balanced decision without manual coordination.

Verify system connectivity before agent execution

Before starting a complex multi-agent session, a coordinator agent runs `check_armano_status` on the MCP Server to verify the API is responsive. This prevents agents from wasting tokens on a disconnected service. Once connectivity is confirmed, the agents proceed to query `list_employees` and allocate tasks. If the status check fails, the coordinator pauses the workflow and alerts your team.

Setup guide

Set up Armano 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 Armano 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="Armano_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install `autogen-ext[mcp]` and use `mcp_server_tools` with `StreamableHttpServerParams` pointing to your Vinkius endpoint. Pass the resulting tools list directly to your `AssistantAgent` constructor.

Yes, you assign the `create_time_entry` tool to a specific agent in your group chat. That agent executes the tool once the other agents agree that the logged hours are valid.

Agents share the output of `get_project` by posting it to the group chat. The other agents read this message, parse the project details, and use that context for their next reasoning step.

Yes, the AutoGen MCP adapter supports both transport protocols. When hosting on Vinkius, you will use the Streamable HTTP transport to connect to your secure endpoint.

All interactions with employee profiles and leave requests are sandboxed in a secure V8 isolate. Vinkius ensures that this MCP Server and your API keys never leave the secure execution context.

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