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

Build automated incident response chains in LangChain by linking Gatus (Health Dashboard) real-time endpoint telemetry.

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Connect Gatus (Health Dashboard) MCP to LangChain

Create your Vinkius account to connect Gatus (Health Dashboard) to LangChain 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 LangChain

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Claude

Perplexity

Chain Gatus data into reasoning loops

Connect `list_endpoints` to your LangChain agent to identify failing services. The agent triggers subsequent logic based on live status codes rather than static logs. This creates a feedback loop where your chain evaluates the severity of an outage. You stop guessing and start acting on the actual state returned by the dashboard.

Automate health checks in LangGraph

Feed `get_endpoint_health` results directly into your graph state to manage complex workflows. The agent decides when to skip or retry tasks depending on the health response. It removes the need for manual monitoring triggers. Your chain handles the investigation step the moment a health probe flips to a warning state.

Trace performance with metric tools

Use `get_metrics` to pull Prometheus-compatible data into your LangSmith traces. You get a clear view of how tool inputs correlate with system latency over time. This visibility ensures you understand exactly why a chain failed. You see the raw metric values alongside the agent's internal reasoning process.

Setup guide

Set up Gatus (Health Dashboard) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Gatus (Health Dashboard) tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "gatus-health-dashboard-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Gatus (Health Dashboard) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Gatus (Health Dashboard) MCP in LangChain

Install the MCP adapters and use the MultiServerMCPClient to point at your hosted endpoint. Once connected, pass the tools into your agent definition to grant it access to your infrastructure data.

Yes. You can write a chain that polls endpoints and sends notifications if health drops. It turns your agent into an active monitor that understands your specific service topology.

It does. You can store the output of these tools in your LangGraph state objects. This allows the agent to recall previous health states during multi-step troubleshooting.

They are. The server supports asynchronous calls, which keeps your chains responsive when polling multiple endpoints simultaneously.

Your instance stays isolated within the Vinkius sandbox. The server only transmits the specific health status and performance metrics requested by the agent, ensuring your underlying infrastructure configs remain private.

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