How to Use the Everbridge Critical Management MCP in Vercel AI SDK

Q: How do I stream Everbridge Critical Management alerts with Vercel AI SDK?

You use the listcriticalnotifications tool inside your Next.js route handler. Pass the Vinkius MCP client tools array to streamText to let your agent fetch and render active alert statuses dynamically.

Q: Can the Vercel AI SDK handle incident timeline queries using Everbridge Critical Management?

Yes, the SDK passes the getincidentdetaileddata tool directly to your model. The model calls the tool, receives the timeline data, and streams the formatted markdown response straight to your chat component.

Q: How do I handle contact lookups during a live incident?

Your agent uses getcontactprofileandmethods to find how to reach a specific engineer. The SDK handles the tool call response and updates your UI with the active phone numbers and emails.

Feed live incident timelines and alert delivery states directly to your web app UI in real-time with Vercel AI SDK.

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Connect Everbridge Critical Management MCP to Vercel AI SDK

Create your Vinkius account to connect Everbridge Critical Management 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 Everbridge Critical Management with Vercel AI SDK

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Build real-time incident dashboards with Vercel AI SDK

The `list_critical_incidents` tool lets your AI client pull active event records during a system outage using this MCP Server. Instead of making users wait for a slow API payload to resolve, the Vercel AI SDK streams these live updates directly into your React components as they arrive. You can pair this with `get_incident_detailed_data` to render granular timelines side-by-side with your chat interface. This keeps your response team updated without manual page refreshes during high-stress outages.

Stream notification delivery status to your interface

The `get_notification_detailed_status` tool queries the exact delivery metrics for active broadcasts. By feeding this tool to your streaming AI client, you can show live charts of SMS and voice call completions directly in the user's browser. This setup relies on Vercel's edge-compatible runtime to keep latency low. You get immediate visibility into who has acknowledged the alert and which communication channels are failing.

Run rapid crisis audits from an edge-ready MCP Server

The `quick_crisis_event_audit` tool aggregates ongoing incidents and recent notification runs into a single high-level summary. When deployed on Vinkius, this MCP Server lets your AI client generate quick operational health summaries at the edge. The SDK takes the tool output and streams the text generation word-by-word. This prevents blocking UI threads, giving your incident commanders immediate answers when seconds count.

Setup guide

Set up Everbridge Critical Management 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 Everbridge Critical Management 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 Everbridge Critical Management transactions",
});

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

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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 Everbridge Critical Management. 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 Everbridge Critical Management MCP in Vercel AI SDK

You use the `list_critical_notifications` tool inside your Next.js route handler. Pass the Vinkius MCP client tools array to `streamText` to let your agent fetch and render active alert statuses dynamically.

Yes, the SDK passes the `get_incident_detailed_data` tool directly to your model. The model calls the tool, receives the timeline data, and streams the formatted markdown response straight to your chat component.

This server runs in Vinkius's secure sandbox, meaning your edge route only needs to make a lightweight HTTP call. The Vercel AI SDK handles this connection without bloating your edge bundle size.

Your agent uses `get_contact_profile_and_methods` to find how to reach a specific engineer. The SDK handles the tool call response and updates your UI with the active phone numbers and emails.

This MCP Server touches sensitive contact profiles, phone numbers, and active incident timelines. Vinkius isolates the execution in a zero-trust V8 sandbox and handles your credentials securely, ensuring no PII is exposed or cached.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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