How to Use the eduMe MCP in AutoGen

Q: How do I register the eduMe MCP Server tools in AutoGen?

You install autogen-extmcp and use the mcpservertools helper with your Vinkius HTTP URL. This automatically converts the server tools into a format your AssistantAgent understands.

Enable multi-agent debate to audit training compliance and course performance using AutoGen.

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Connect eduMe MCP to AutoGen

Create your Vinkius account to connect eduMe 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 eduMe with AutoGen

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Run collaborative compliance audits with an MCP Server

The `quick_team_training_audit` tool retrieves high-level activity summaries and member counts for your training groups. In AutoGen, a compliance agent calls this tool to spot teams with low completion rates. A separate manager agent then reviews the output and proposes a follow-up strategy. This multi-agent debate ensures that you don't just find the gaps, but also formulate the right response based on actual data.

Search and evaluate trainees via multi-agent debate

The `search_trainees_by_keyword` tool searches for registered training users by name or external ID. Your search agent locates the trainee, then passes their ID to an analysis agent. The analysis agent runs `get_user_training_profile` to evaluate their history. If the profile reveals incomplete modules, the agents debate whether to send a direct message or escalate the compliance gap to a manager.

Audit account limits and course configurations in AutoGen

The `get_edume_account_metadata` tool retrieves the metadata and limits for your account. Your system agent checks these limits before initiating a bulk training push. Meanwhile, a content agent calls `list_training_courses` to verify that the active courses fit within those limits. This prevents API throttling and ensures your automated training pipelines run without unexpected interruptions.

Setup guide

Set up eduMe 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 eduMe 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="eduMe_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You install `autogen-ext[mcp]` and use the `mcp_server_tools` helper with your Vinkius HTTP URL. This automatically converts the server tools into a format your AssistantAgent understands.

Yes, you can pass the tool list to multiple agents in your group chat. For example, one agent can search for users while another pulls their training profiles.

The agents discuss the tool outputs in their conversation thread. If `list_top_performing_courses` conflicts with internal team metrics, the agents debate the discrepancy until they reach a consensus.

Yes, the MCP integration supports both stdio and Streamable HTTP transports. Vinkius secures the connection, allowing your agents to communicate with the API without local setup.

Yes, all data transmission is encrypted in transit. The trainee profiles, names, and course records retrieved by the agents are processed in an isolated V8 sandbox, preventing unauthorized access or data leakage.

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