How to Use the Honeybadger (Error Tracking) MCP in Vercel AI SDK

Q: How do I stream faults from Honeybadger (Error Tracking) into my Vercel AI SDK app?

After setting up the mcpClient, pass the listfaults tool to streamText. The Vercel AI SDK will stream the JSON results, which you can then parse and render into your React or Next.js components in real-time.

Q: Can I resolve errors in Honeybadger (Error Tracking) using the Vercel AI SDK?

Yes. The resolvefault tool lets you mark a fault as resolved directly from your application's interface. Since this is a permanent change, you should always trigger this tool from an explicit user action, like clicking a 'Resolve' button.

Q: What's the best way to show deployment history from Honeybadger (Error Tracking) with the Vercel AI SDK?

Use the listdeployments tool. Your agent can fetch the list and stream it to the client. You can then display this alongside data from listfaults to help developers see which deployment might have introduced a new error.

Connect your Vercel AI SDK app to Honeybadger. Stream error data directly into your UI components without waiting for spinners.

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Connect Honeybadger (Error Tracking) MCP to Vercel AI SDK

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Setup Honeybadger (Error Tracking) with Vercel AI SDK

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Live Error Dashboard in Your UI

Build a custom monitoring dashboard right inside your own application. Use the Vercel AI SDK to stream results from `list_projects` and `list_faults` directly into your React or Svelte components. Your users see a live feed of application health, not a static page. When a user clicks an error, you can instantly fetch the details. Call `get_fault` to get the full stack trace and `list_notices` to see every occurrence. Because it's streaming, the data populates on screen as it arrives.

Correlate Deployments and Faults

Figure out which deploy broke the build. This MCP Server lets your agent pull deployment history straight from Honeybadger. Your agent can call `list_deployments` to get a list of recent pushes. Then, cross-reference that with the output from `list_faults`. You can build a simple UI that shows new faults appearing right after a specific deployment went out. It's a fast way to pinpoint regressions.

Triage Errors from Your Own App

Give your support team the tools to manage errors without leaving your internal admin panel. This MCP server exposes a `resolve_fault` tool. It's an irreversible action, so you'll want to put it behind a confirmation button in your UI. You can also get context on who's on the team with `list_members` or check on uptime monitors with `list_sites`. It's all there, ready to be wired into your Vercel AI SDK-powered interface.

Setup guide

Set up Honeybadger (Error Tracking) 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 Honeybadger (Error Tracking) 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 Honeybadger (Error Tracking) 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 Honeybadger. 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 Honeybadger (Error Tracking) MCP in Vercel AI SDK

After setting up the `mcpClient`, pass the `list_faults` tool to `streamText`. The Vercel AI SDK will stream the JSON results, which you can then parse and render into your React or Next.js components in real-time.

Yes. The `resolve_fault` tool lets you mark a fault as resolved directly from your application's interface. Since this is a permanent change, you should always trigger this tool from an explicit user action, like clicking a 'Resolve' button.

Use the `list_deployments` tool. Your agent can fetch the list and stream it to the client. You can then display this alongside data from `list_faults` to help developers see which deployment might have introduced a new error.

It returns the full fault details from Honeybadger. This includes the class name, message, complete stack trace, occurrence count, and environment data. It's everything you need to debug the issue.

Your data, including project details and fault stack traces, is only passed between Honeybadger and your AI client through our ephemeral, sandboxed server. We don't store your API keys or any of the data that passes through. Authentication is handled by a single Vinkius token.

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