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

Q: Can CrewAI agents use Lacework (Cloud Security & CNAPP) to audit multiple accounts?

Yes. By using searchcloudinventory and listresourcegroups, your agents can cycle through different AWS accounts and resource sets to maintain a full security audit.

Q: Is it possible to filter Lacework (Cloud Security & CNAPP) tools in CrewAI?

You can use the toolfilter option in your agent definitions. This restricts which tools an agent can call, ensuring that only authorized agents can execute sensitive queries.

Deploy autonomous security response teams using the Lacework (Cloud Security & CNAPP) MCP Server with CrewAI.

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Connect Lacework (Cloud Security & CNAPP) MCP to CrewAI

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

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Autonomous threat hunting with CrewAI

Assign a research agent to continuously scan for threats using `search_cve_exposure`. When the agent identifies a vulnerable node, it passes the context to a moderator agent for review. This collaborative approach allows you to scale your security operations without adding headcount. Your crew handles the identification and prioritization of risks around the clock.

Deep security policy auditing

Task your agents with checking global compliance by calling `list_security_policies`. They can then cross-reference these policies against your current cloud inventory found via `search_cloud_inventory`. This gives you a clear picture of your security posture across the entire organization. Your agents report back only on the discrepancies that matter, saving you from manual audit fatigue.

Real-time incident response for CrewAI

Use `search_alerts` to feed your agents the latest Kubernetes execution anomalies. The agents then collaborate to determine if an exfiltration attempt is real or a routine system process. By leveraging the shared memory of your crew, they can build a timeline of events. This gives you a comprehensive view of the incident before you decide how to respond.

Setup guide

Set up Lacework (Cloud Security & CNAPP) MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Lacework (Cloud Security & CNAPP) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Lacework (Cloud Security & CNAPP) Analyst",
    goal="Access and analyze Lacework (Cloud Security & CNAPP) data via MCP.",
    backstory="Expert analyst with direct Lacework (Cloud Security & CNAPP) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Lacework (Cloud Security & CNAPP) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Lacework (Cloud Security & CNAPP) Analyst",
        goal="Access and analyze Lacework (Cloud Security & CNAPP) data via MCP.",
        backstory="Expert analyst with direct Lacework (Cloud Security & CNAPP) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Lacework (Cloud Security & CNAPP) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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

Agents share context through a common memory space. One agent fetches an alert with `get_alert`, and the next agent analyzes the payload to determine the severity.

Yes. By using `search_cloud_inventory` and `list_resource_groups`, your agents can cycle through different AWS accounts and resource sets to maintain a full security audit.

You can use the tool_filter option in your agent definitions. This restricts which tools an agent can call, ensuring that only authorized agents can execute sensitive queries.

You structure your crew with a human-in-the-loop moderator. The research agent finds the issue, but the moderator requires your explicit final approval before any remediation occurs.

The server only processes cloud resource inventory, vulnerability scan results, and security alert metadata. It never accesses your internal business logic, user identities, or application-level data.

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