Can I see failing services across all my hosts?

Yes! Use the `list_all_monitored_services` tool. The agent will return a comprehensive list of services, and you can ask it to filter for those in CRITICAL or WARNING states.

How do I apply changes I made in WATO through the agent?

Use the `activate_checkmk_changes` tool. Your agent will trigger the activation process in Checkmk, pushing all pending configurations to the monitoring core.

Where do I find my Checkmk Automation Secret?

Log in to your Checkmk site, go to 'Setup' -> 'Users', and edit your automation user. You will see the 'Automation secret' field there.

Checkmk MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Checkmk
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Checkmk through Vinkius, pass the Edge URL in the `mcps` parameter and every Checkmk tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Checkmk Specialist",
    goal="Help users interact with Checkmk effectively",
    backstory=(
        "You are an expert at leveraging Checkmk tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Checkmk "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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High SecurityEnterprise-grade

IAMAccess control

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V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Checkmk MCP Server

Connect your Checkmk site to any AI agent and take full control of your IT infrastructure monitoring through natural conversation. Streamline how you manage complex server landscapes and service states.

When paired with CrewAI, Checkmk becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Checkmk tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Host Oversight — List and retrieve detailed configuration and status for all monitored hosts natively
Service Intelligence — Access real-time monitoring data for services across your entire infrastructure flawlessly
Configuration Control — List folders, host groups, and service groups to understand your monitoring structure securely
Change Management — Manually activate pending configuration changes directly within your workspace flawlessly
Live Diagnostics — Retrieve plugin output and current states for specific services to troubleshoot issues in real-time
System Metadata — Access core site information and organizational configurations directly within your workspace

The Checkmk MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Checkmk to CrewAI via MCP

Follow these steps to integrate the Checkmk MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Checkmk

Why Use CrewAI with the Checkmk MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Checkmk through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Checkmk + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Checkmk MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Checkmk for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Checkmk, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Checkmk tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Checkmk against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Checkmk MCP Tools for CrewAI (8)

These 8 tools become available when you connect Checkmk to CrewAI via MCP:

activate_checkmk_changes

Activate pending configuration changes in Checkmk

get_host_details

Get detailed information for a specific host

list_all_monitored_services

List all services across all hosts

list_checkmk_folders

List configuration folders

list_checkmk_hosts

List all monitored hosts

list_host_groups

List configured host groups

list_host_services

List all monitored services for a specific host

list_service_groups

List configured service groups

Example Prompts for Checkmk in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Checkmk immediately.

"List all my hosts in Checkmk."

"Show me the services for host 'web-server-01' that are not OK."

"Activate my pending changes in Checkmk."

Troubleshooting Checkmk MCP Server with CrewAI

Common issues when connecting Checkmk to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Checkmk + CrewAI FAQ

Common questions about integrating Checkmk MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.