How to Use the Lacework (Cloud Security & CNAPP) MCP in AutoGen

Q: How do I register the Lacework (Cloud Security & CNAPP) MCP Server tools in AutoGen?

Install autogen-extmcp and use mcpservertools with your Vinkius HTTP endpoint parameter. Pass the returned tools directly to your AssistantAgent constructor to start using them.

Q: Can AutoGen agents negotiate remediation steps for alerts found in Lacework (Cloud Security & CNAPP)?

Yes, one agent can fetch alert payloads via getalert while another analyzes the affected assets using searchcloudinventory. They discuss the findings to agree on the safest remediation path.

Q: How is the privacy of my Lacework LQL queries protected in this setup?

Custom queries executed via executequery are processed within secure, isolated sandboxes. Your LQL syntax and the resulting telemetry are never exposed to external networks or used to train public models.

Build multi-agent security teams in AutoGen that debate active cloud alerts and plan automated remediation with this MCP Server.

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Connect Lacework (Cloud Security & CNAPP) MCP to AutoGen

Create your Vinkius account to connect Lacework (Cloud Security & CNAPP) 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 Lacework (Cloud Security & CNAPP) with AutoGen

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Multi-agent debate on active Kubernetes alerts

The `search_alerts` tool retrieves events involving anomalous Kubernetes executions or container network exfiltrations. Within AutoGen, a dedicated security analyst agent can present these alerts to a system administrator agent to debate the risk level of the activity. This conversational structure prevents hasty, automated teardowns of critical infrastructure. The agents negotiate whether an alert indicates a true compromise or expected developer behavior before taking any action.

Automated vulnerability triage using AutoGen MCP Server tools

The `list_container_vulnerabilities` tool inspects registries for static image vulnerabilities before CI/CD promotion. Your AutoGen QA agent can run this check, then debate with a release agent about whether the severity justifies blocking the deployment. By automating this negotiation, you stop high-risk vulnerabilities from reaching production without slowing down safe releases. The entire debate and decision process is logged, leaving a clear audit trail for your security compliance reviews.

Automated validation of open security perimeters

The `search_cloud_inventory` tool enumerates running instances and active networking perimeters, such as unrestricted S3 buckets. An AutoGen network auditor agent uses this tool to flag open ports, prompting a compliance agent to verify if a policy exception exists. This continuous debate ensures that temporary development configurations do not turn into permanent security holes. Your agents collaborate to identify, verify, and document network exposure without human supervision.

Setup guide

Set up Lacework (Cloud Security & CNAPP) 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 Lacework (Cloud Security & CNAPP) 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="Lacework (Cloud Security & CNAPP)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Lacework (Cloud Security & CNAPP) 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="Lacework (Cloud Security & CNAPP)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Lacework (Cloud Security & CNAPP) 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 Lacework. 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 Lacework (Cloud Security & CNAPP) MCP in AutoGen

Install `autogen-ext[mcp]` and use `mcp_server_tools` with your Vinkius HTTP endpoint parameter. Pass the returned tools directly to your `AssistantAgent` constructor to start using them.

Yes, one agent can fetch alert payloads via `get_alert` while another analyzes the affected assets using `search_cloud_inventory`. They discuss the findings to agree on the safest remediation path.

The adapter automatically translates the server's JSON schemas into the format AutoGen expects. This ensures your agents can call tools like `search_cve_exposure` with the correct arguments out of the box.

You can connect using either stdio or Streamable HTTP transports. When hosted on Vinkius, you will use the secure HTTP endpoint with your personal access token.

Custom queries executed via `execute_query` are processed within secure, isolated sandboxes. Your LQL syntax and the resulting telemetry are never exposed to external networks or used to train public models.

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