How to Use the Senar.io MCP in AutoGen

Q: How do I register the Senar.io MCP Server tools with my AutoGen agents?

Install the autogen-extmcp extension to load the MCP tools and use the mcpservertools helper to fetch the tool definitions. Pass this tool list to your AssistantAgent constructor to expose them to the conversation loop.

Q: How is my organization's user directory protected during agent execution?

Your user directory data accessed via listusers is never stored by the framework or the adapter. All calls run through a zero-trust sandbox with point-to-point encryption, keeping your roster completely confidential.

Let specialized AutoGen agents debate and manage simulator assignments using this MCP Server.

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Connect Senar.io MCP to AutoGen

Create your Vinkius account to connect Senar.io to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Senar.io with AutoGen

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Multi-agent coordination for user assignments

The `create_user_and_assign` tool allows your primary agent to register new users and assign them to specific AR collections. In an AutoGen setup, a registration agent can propose a user creation, while a compliance agent reviews the assignment details. They debate the user's eligibility and clean up the mess before executing the tool call. This consensus-driven approach prevents incorrect assignments and maintains directory hygiene. The compliance agent uses `list_users` to verify if the user already exists in another group. Only when both agents agree does the system trigger the actual creation.

Debate training performance using AutoGen

The `get_activity_data` tool retrieves raw training results that your agents can analyze from different angles. A performance agent might look for speed, while a safety agent focuses on accuracy metrics. They discuss the results to form a balanced evaluation of the user's simulator run. Once they reach a consensus, they call `add_content` to append their collective notes and feedback to the user's training collection. This automated review process ensures that evaluations are thorough and based on multiple distinct criteria.

Monitor active sessions with this AutoGen MCP Server

The `get_user_sessions` tool outputs live runtime data that helps your agents track simulator usage. A scheduling agent can flag sessions that run too long, while a resource agent checks if simulator capacity is reaching its limit. They negotiate whether to terminate or extend specific runs. To make an informed decision, they query `get_progress` to see if the user is close to finishing their module. This multi-agent deliberation prevents premature session cutoffs while maintaining optimal resource allocation across your infrastructure.

Setup guide

Set up Senar.io 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 Senar.io 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="Senar.io_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install the `autogen-ext[mcp]` extension to load the MCP tools and use the `mcp_server_tools` helper to fetch the tool definitions. Pass this tool list to your `AssistantAgent` constructor to expose them to the conversation loop.

Yes, one agent can draft the assignment parameters while another agent validates them against your organizational policies before triggering the tool.

The agents use their respective system prompts to evaluate the activity logs from different perspectives, debating the outcome in the chat log until they converge on a single evaluation score.

Yes, the adapter handles both transport modes, allowing your AutoGen agents to communicate with the server hosted securely on the Vinkius platform.

Your user directory data accessed via `list_users` is never stored by the framework or the adapter. All calls run through a zero-trust sandbox with point-to-point encryption, keeping your roster completely confidential.

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