How to Use the Gatus (Health Dashboard) MCP in CrewAI

Q: How do I configure Gatus (Health Dashboard) tools for my CrewAI agents?

Pass your Vinkius endpoint directly into the mcps array when defining your agent. The framework automatically parses the available tools and assigns them to that specific crew member.

Q: How do I filter which Gatus (Health Dashboard) tools a CrewAI agent can use?

Import MCPServerHTTP from crewai.mcp and use the toolfilter parameter. This restricts your monitor agent to only see listendpoints, preventing it from pulling heavy Prometheus payloads.

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Connect Gatus (Health Dashboard) MCP to CrewAI

Create your Vinkius account to connect Gatus (Health Dashboard) 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 Gatus (Health Dashboard) with CrewAI

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Multi-agent monitoring via MCP Server

The `list_endpoints` tool gives your CrewAI monitor agent a bird's-eye view of your entire stack. This agent runs continuously, scanning the array for any service returning a non-200 status. When it finds a failure, it passes the target URL via shared memory to an analyst agent. The analyst takes over, calling `get_endpoint_health` to build a timeline of the outage.

Isolate performance bottlenecks

Your analyst agent uses `get_endpoint_stats` to pull detailed latency and response metrics. It compares these numbers against baseline expectations to determine if the issue is a hard down or just severe degradation. Because the agents share context, the analyst hands a complete diagnostic report to a responder agent. The responder decides whether to restart a service or page the on-call rotation.

Autonomous telemetry analysis

The `get_metrics` tool exposes raw Prometheus data to your specialized data-crunching agents. They ingest the system-wide telemetry to find correlations between isolated endpoint failures. You build a hierarchical crew where a manager agent oversees the process. The manager delegates the scraping tasks, reviews the findings, and outputs a final incident summary without human intervention.

Setup guide

Set up Gatus (Health Dashboard) 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 Gatus (Health Dashboard) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Gatus (Health Dashboard) 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 Gatus. 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 Gatus (Health Dashboard) MCP in CrewAI

Pass your Vinkius endpoint directly into the `mcps` array when defining your agent. The framework automatically parses the available tools and assigns them to that specific crew member.

Yes. You assign the server to specific agents based on their roles. A monitor agent handles the broad checks, while an analyst agent digs into the specific metrics.

Import `MCPServerHTTP` from `crewai.mcp` and use the `tool_filter` parameter. This restricts your monitor agent to only see `list_endpoints`, preventing it from pulling heavy Prometheus payloads.

CrewAI agents manage their own tool execution retries. If the HTTP transport drops, the agent will attempt the call again based on its internal logic.

The MCP Server accesses raw telemetry data but operates entirely within a restricted V8 Isolate. The connection is stateless, meaning your metrics are wiped from memory the second the agent finishes its task.

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