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

Q: Can I restrict which Lacework (Cloud Security & CNAPP) tools my Google ADK agent can access?

Yes. Use the toolnames filter when initializing the McpToolset to expose only specific tools, like limiting the agent to searchcveexposure while blocking executequery.

Q: How does Gemini's long context handle Lacework (Cloud Security & CNAPP) data within Google ADK?

The model can ingest the entire JSON output from searchalerts and searchcloudinventory at once. This allows the agent to find hidden patterns across thousands of cloud resources in a single run.

Q: Can I join Lacework security alerts with BigQuery data using this setup?

Absolutely. Your agent can fetch live alert details via getalert and immediately query your BigQuery security lake to cross-reference the offending IP addresses or container SHAs. This MCP workflow keeps all security data unified.

Equip Google ADK agents with Lacework tools to analyze massive cloud vulnerability datasets in Gemini's long-context window.

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Connect Lacework (Cloud Security & CNAPP) MCP to Google ADK

Create your Vinkius account to connect Lacework (Cloud Security & CNAPP) to Google ADK 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 Google ADK

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Analyze massive cloud inventories in Gemini

Feed your entire cloud topology into Gemini's million-token context window. This MCP Server lets your Google ADK agent run `search_cloud_inventory` to pull running instances and active networking perimeters directly into your enterprise pipeline. The agent correlates this live asset data with BigQuery security tables, mapping unrestricted S3 buckets or open firewall ports. You get a complete, context-aware risk profile without manual data export.

Verify cloud policy compliance using Google ADK

Ensure your multi-cloud infrastructure matches your corporate security baselines. Our MCP Server lets the agent query `list_security_policies` to pull active rules, then uses `list_resource_groups` to segment checks between staging and production environments. If a policy violation is detected, the agent writes the compliance gap to Vertex AI for remediation planning. This keeps your security posture updated without manual audits.

Investigate container threats with long-context reasoning

Run deep post-mortem analyses of container security events. Your agent uses `list_container_vulnerabilities` and `get_alert` to gather filesystem-level CVE data and behavioral payloads from your registries. Because Gemini handles huge payloads, the agent can ingest hours of telemetry from `search_alerts` to trace container network exfiltration paths. It maps the attack vector from the registry to the running cluster.

Setup guide

Set up Lacework (Cloud Security & CNAPP) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Lacework (Cloud Security & CNAPP) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Lacework (Cloud Security & CNAPP)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Lacework (Cloud Security & CNAPP) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Lacework (Cloud Security & CNAPP) MCP in Google ADK

Instantiate an McpToolset pointing to the Vinkius HTTP endpoint. Pass this toolset into your LlmAgent to give Gemini direct access to all Lacework security tools.

Yes. Use the tool_names filter when initializing the McpToolset to expose only specific tools, like limiting the agent to `search_cve_exposure` while blocking `execute_query`.

The model can ingest the entire JSON output from `search_alerts` and `search_cloud_inventory` at once. This allows the agent to find hidden patterns across thousands of cloud resources in a single run.

Absolutely. Your agent can fetch live alert details via `get_alert` and immediately query your BigQuery security lake to cross-reference the offending IP addresses or container SHAs. This MCP workflow keeps all security data unified.

The server handles sensitive cloud inventory data and alert payloads. Vinkius secures this by running the MCP Server in an ephemeral, zero-trust V8 sandbox with encrypted token handling.

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