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

Index your infrastructure health with LlamaIndex using Gatus (Health Dashboard) data for grounded, queryable insights.

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Connect Gatus (Health Dashboard) MCP to LlamaIndex

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

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Perplexity

Vectorize your infrastructure state

Use `get_endpoint_stats` to feed performance data into your LlamaIndex knowledge base. Your agent now searches past stats to find patterns in service degradation. It moves beyond simple alerts. You get a searchable history of system behavior that informs how the agent answers questions about recent downtime.

Ground answers in live API telemetry

Retrieve `list_endpoints` data to create a dynamic context for your RAG pipeline. The agent queries your live dashboard instead of relying on stale documentation. This ensures your responses reflect the current reality of your deployment. If a service is down, your agent knows it before you even ask.

Build queryable health indexes

Map `get_metrics` output to a document index for long-term trend analysis. Your agent performs semantic searches across your performance history to detect recurring bottlenecks. It turns raw numbers into actionable knowledge. You can ask questions about which services perform worst during peak load and get grounded answers.

Setup guide

Set up Gatus (Health Dashboard) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Gatus (Health Dashboard) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Gatus (Health Dashboard) tools.",
)
response = await agent.run("List recent Gatus (Health Dashboard) data")

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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 LlamaIndex

Use the llama-index-tools-mcp package to initialize the client. Once the tools are indexed, your agent treats Gatus (Health Dashboard) data as just another source of truth.

It can. By indexing the tool outputs into a vector store, you allow the agent to look back at previous health results and performance trends.

Everything is contained within your private index. No telemetry or health data is shared outside your environment, and the Vinkius sandbox ensures the connection remains encrypted.

It does. You pass the tool list directly to your FunctionAgent, allowing it to call endpoints as needed during the retrieval process.

The server only exposes endpoint status codes, response times, and Prometheus metrics. Access is strictly limited to these fields, keeping your sensitive auth tokens or internal IP schemas hidden.

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