How to Use the KnowBe4 (KMSAT Reporting) MCP in AutoGen

Deploy AutoGen multi-agent squads to audit your KnowBe4 (KMSAT Reporting) logs and debate risk remediation strategies.

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Connect KnowBe4 (KMSAT Reporting) MCP to AutoGen

Create your Vinkius account to connect KnowBe4 (KMSAT Reporting) 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 KnowBe4 (KMSAT Reporting) with AutoGen

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Run multi-agent debates on security risks

`get_account_risk_score` gives your primary auditor agent the raw numbers to start a security review. A separate compliance agent then challenges these findings by pulling detailed reports. The agents debate whether to focus on immediate remediation or broad training. They use the risk score to ground their arguments in actual organizational threat levels.

Coordinate group audits using an MCP Server

`list_groups` allows your coordinator agent to map out all departments for the auditing squad. The auditor agent then queries `list_user_groups` for specific high-risk individuals to see where they belong. By dividing the work, one agent can focus on department-level trends while another looks at individual performance. They compile their findings into a single, unified report.

Analyze phishing test failures cooperatively

`list_phishing_tests` provides the master list of campaigns for your analysis agents. One agent pulls specific test configurations using `get_phishing_test_details` to study the templates used. Another agent checks the raw results with `list_phishing_store_results` to see which departments fell for the test. Together, they negotiate the best training campaign to launch next.

Setup guide

Set up KnowBe4 (KMSAT Reporting) 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 KnowBe4 (KMSAT Reporting) 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="KnowBe4 (KMSAT Reporting)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent KnowBe4 (KMSAT Reporting) 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="KnowBe4 (KMSAT Reporting)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent KnowBe4 (KMSAT Reporting) data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about KnowBe4 (KMSAT Reporting) MCP in AutoGen

Use the AutoGen MCP extension to fetch the tool definitions from your Vinkius endpoint. Pass the resulting tool list to your AssistantAgent constructor so the agent can call `list_users` during conversations.

Yes, agents share access to the toolset and can invoke tools like `list_training_campaigns` as needed. The conversation history keeps track of which agent called which tool and what data was returned.

Agents use structured debate to compare high-level metrics from `get_account_risk_score` with granular user data from `get_user_details`. They negotiate a consensus based on your custom system instructions.

Yes, the AutoGen MCP adapter handles both transport protocols. For production setups, the HTTP transport connects your multi-agent team to the managed Vinkius hosting endpoint securely.

All transactions involving training statuses, user lists, and phishing test metrics run inside zero-trust sandbox isolates. Vinkius handles the underlying authentication, ensuring your API tokens never pass through the LLM context.

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