How to Use the Gatus (Health Dashboard) MCP in Vercel AI SDK

Q: How do I connect the Gatus (Health Dashboard) to the Vercel AI SDK?

Install @ai-sdk/mcp. Use createMCPClient with an HTTP transport pointing to your Vinkius endpoint. Pass the client's tools directly into streamText or generateText.

Q: Can I stream Gatus (Health Dashboard) status updates using the Vercel AI SDK?

Yes. The SDK streams the output of getendpointhealth straight to your frontend. Your users watch the AI evaluate the incident history in real-time.

Stream live Gatus infrastructure health straight into your React frontends using the Vercel AI SDK.

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Connect Gatus (Health Dashboard) MCP to Vercel AI SDK

Create your Vinkius account to connect Gatus (Health Dashboard) to Vercel AI SDK 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 Vercel AI SDK

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Claude

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Stream metrics via MCP Server

The `get_metrics` tool pulls raw Prometheus-compatible telemetry directly from your Gatus instance. Your Vercel AI SDK client streams this data straight to the user's browser without waiting for the entire payload to resolve. You build a dashboard where the end user watches the AI parse infrastructure health live. No loading spinners, just raw data populating the UI as the agent reads it.

Map endpoint health to React components

The `list_endpoints` tool returns the current status of every monitored service. You pass this to your Next.js frontend, letting the AI generate dynamic status badges based on the live array. If a service looks degraded, the agent calls `get_endpoint_health` to fetch the recent check history. It streams the incident context directly into a chat window or a dedicated incident response component.

Render performance stats instantly

Use `get_endpoint_stats` to grab latency and response time statistics for specific targets. The SDK feeds these numbers into your visualization components as fast as the agent retrieves them. Edge functions can trigger these checks on page load. The user sees exact millisecond response times and failure rates immediately, keeping your status pages perfectly synced with Gatus.

Setup guide

Set up Gatus (Health Dashboard) MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Gatus (Health Dashboard) tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Gatus (Health Dashboard) transactions",
});

console.log(text);
await mcpClient.close();

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 Vercel AI SDK

Install `@ai-sdk/mcp`. Use `createMCPClient` with an HTTP transport pointing to your Vinkius endpoint. Pass the client's tools directly into `streamText` or `generateText`.

Yes. The SDK streams the output of `get_endpoint_health` straight to your frontend. Your users watch the AI evaluate the incident history in real-time.

Vinkius handles the underlying server authentication. You just provide your endpoint token to your MCP client. If you need user-level auth, configure `authProvider` in your setup.

The SDK streams whatever text the agent generates while waiting. You can also configure timeouts on the transport layer to prevent hanging requests.

This MCP Server only reads Prometheus metrics and endpoint URLs. It runs inside an ephemeral V8 Isolate Sandbox that destroys itself after the request. Zero data persists on disk.

Use it with your favorite AI tools

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