How to Use the CrowdSec MCP in CrewAI

Q: How do I configure CrewAI to use the CrowdSec MCP Server?

Install the framework with pip install crewai 'crewaitools'. You can then pass your Vinkius CrowdSec URL directly into the mcps array of your Agent configuration.

Deploy a team of autonomous CrewAI security agents to monitor CrowdSec threat alerts with this MCP Server.

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Connect CrowdSec MCP to CrewAI

Create your Vinkius account to connect CrowdSec 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 CrowdSec with CrewAI

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Multi-agent threat hunting via MCP Server

The `get_cti_smoke` tool gives your security crew access to global IP reputation data. You can assign a specialized researcher agent to analyze suspicious logs and check them against CrowdSec's global database. This MCP Server allows the researcher agent to pass reputation scores to an analyst agent. The crew can then collaborate to decide whether an IP represents a targeted attack or random background noise.

Autonomous decision auditing with CrewAI

The `get_decisions` tool allows your agents to query your local CrowdSec instance for active blocks. A moderator agent can watch your network alerts and cross-reference them with these local decisions. Instead of a human manually checking firewall logs, your CrewAI team operates autonomously. The agents can verify if local blocks are working correctly and escalate anomalies to your engineering Slack channel.

Continuous threat streaming with CrewAI

The `get_decisions_stream` tool lets your agent pool watch for newly added or deleted decisions. This continuous feed keeps your entire crew aligned on the current threat landscape. When a new ban is streamed, a mitigation agent can immediately update cloud security groups. This multi-agent coordination ensures your active defenses update as soon as CrowdSec flags an attacker.

Setup guide

Set up CrowdSec 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 CrowdSec tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent CrowdSec 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 CrowdSec. 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 CrowdSec MCP in CrewAI

Install the framework with pip install crewai 'crewai[tools]'. You can then pass your Vinkius CrowdSec URL directly into the mcps array of your Agent configuration.

Yes. You can use the MCPServerHTTP class from crewai.mcp and apply a tool_filter to only expose specific tools like get_cti_smoke to certain agents.

Yes. You can design a sequential process where Agent A checks an IP using get_cti_smoke, and Agent B uses those results to query local decisions via get_decisions.

The integration supports stdio, SSE, and Streamable HTTP transports, allowing your CrewAI setup to connect to Vinkius from local environments or cloud pipelines.

Yes. All queries for local decisions and IP reputation are run through an isolated, zero-trust Vinkius sandbox. Your raw security logs and LAPI credentials are never exposed to the LLM or stored on Vinkius.

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