How to Use the Drata MCP in CrewAI

Q: Is there a way to filter Drata tools for specific CrewAI agents?

Use the toolfilter option in your configuration. This ensures each agent only sees the tools necessary for its specific role, such as only accessing personnel tools.

Deploy autonomous agent crews to monitor your security posture with this Drata MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Drata MCP to CrewAI

Create your Vinkius account to connect Drata 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.

GDPR Free for Subscribers

Setup Drata with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous monitoring crews for CrewAI

Assign a specialized agent to monitor your cloud infrastructure using `drata_list_assets` and `drata_list_tests`. This agent keeps a constant watch on your security state, flagging deviations for a secondary moderation agent to review. This hierarchical setup allows for continuous oversight. Your crew works in the background, ensuring your AWS, GitHub, and Okta integrations remain compliant with your defined controls.

Security audit crews for CrewAI

Create a team of agents dedicated to audit preparation. One agent can query `drata_list_frameworks` to identify gaps, while another uses `drata_get_control` to gather specific evidence for your auditors. This divides the workload of audit readiness. You spend less time gathering files and more time addressing the actual security findings detected by your agents.

Personnel security crews for CrewAI

Deploy agents to manage your human-centric security requirements. By analyzing `drata_list_personnel`, your agents identify non-compliant devices or incomplete training, escalating these issues only when necessary. This keeps your compliance posture clean without human intervention. Your agents handle the routine checks, ensuring everyone meets the security standards defined in your Drata workspace.

Setup guide

Set up Drata 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 Drata tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Drata 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="Drata Analyst",
        goal="Access and analyze Drata data via MCP.",
        backstory="Expert analyst with direct Drata access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Drata 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Drata. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Drata now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Drata MCP in CrewAI

Pass the server URL directly into your agent definition. This allows your agents to access the full suite of Drata tools during their execution.

Yes. You can design a multi-agent crew where one agent retrieves data from `drata_list_policies` and another analyzes it to report on audit readiness.

Use the tool_filter option in your configuration. This ensures each agent only sees the tools necessary for its specific role, such as only accessing personnel tools.

The MCP protocol ensures that your data stays within the secure connection between the server and your crew. No sensitive info like training completion dates is stored externally.

The server provides the data needed to identify issues. Your agents can then be configured to trigger alerts or suggest remediation steps based on the retrieved status.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript