How to Use the Checkmarx MCP in CrewAI

Q: How do I connect the Checkmarx MCP Server to a CrewAI agent?

Run pip install crewai "crewaitools". Then pass your Vinkius endpoint URL directly into the mcps array parameter when defining your agent.

Q: Can CrewAI filter which Checkmarx MCP tools an agent sees?

You can use MCPServerHTTP from crewai.mcp and apply a toolfilter. This lets you restrict a junior agent to getproject while giving a senior agent access to runscan.

Q: How do I list historical Checkmarx scans in CrewAI?

Give your agent access to listscans. It can fetch completed, running, or canceled jobs, then use the scan IDs to pull actual vulnerability data.

Deploy autonomous CrewAI security teams to trigger Checkmarx MCP Server scans, analyze vulnerabilities, and isolate best fix locations.

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Connect Checkmarx MCP to CrewAI

Create your Vinkius account to connect Checkmarx 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 Checkmarx with CrewAI

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Autonomous AppSec Triage Teams

`get_scan_results` downloads SAST findings and vulnerability severities for your CrewAI agent. You can assign one researcher agent to pull these urgent flaws while a separate analyst agent reviews the exact lines of code. This shared memory approach means your crew works together. The analyst uses `list_bfl` to find the precise fix location, then hands that context off to a reporting agent.

Manage Checkmarx MCP Server Scans

`run_scan` lets your CI/CD monitor agent assert security quality on new pull requests. The agent queues the scan automatically without human intervention. If a developer pushes a new commit overlapping the running job, the moderator agent steps in. It calls `cancel_scan` to drop the old context and prevent unnecessary engine resource consumption.

Audit Infrastructure as Code

`get_kics_results` targets Terraform and CloudFormation misconfigurations instead of standard application flaws. Your infrastructure agent uses this to monitor cloud deployments. To keep everything organized, `list_applications` groups these findings into overarching containers. Then `get_scan_details` provides granular execution timings for every KICS engine that fired.

Setup guide

Set up Checkmarx 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 Checkmarx tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Run `pip install crewai "crewai[tools]"`. Then pass your Vinkius endpoint URL directly into the `mcps` array parameter when defining your agent.

You can use `MCPServerHTTP` from `crewai.mcp` and apply a `tool_filter`. This lets you restrict a junior agent to `get_project` while giving a senior agent access to `run_scan`.

Give your agent access to `list_scans`. It can fetch completed, running, or canceled jobs, then use the scan IDs to pull actual vulnerability data.

The framework supports stdio, SSE, and Streamable HTTP transports. You configure this based on your specific deployment environment.

This integration reads urgent vulnerability severities and exact source code flaws. Vinkius executes these requests inside a hardened, ephemeral V8 sandbox, ensuring your application risk reports disappear the millisecond the request completes.

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