Honeybadger (Error Tracking) MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Honeybadger (Error Tracking) through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Honeybadger (Error Tracking), list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Honeybadger (Error Tracking) MCP Server
Connect your Honeybadger account to any AI agent and take full control of your exception monitoring and application health through natural conversation.
The Vercel AI SDK gives every Honeybadger (Error Tracking) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Project Management — List all monitored projects and extract high-level details including API keys, languages, and unresolved fault counts directly from your agent
- Fault Analysis — Query fault groups (error aggregates) to understand class names, messages, and environment distributions across your infrastructure
- Resolution Workflow — Mark faults as resolved or ignore them to maintain a clean error dashboard and ensure your team stays focused on critical issues
- Notice Inspection — Deep-dive into individual error occurrences (notices) to retrieve backtraces, request data, session context, and server environments
- Uptime & Deployment — Monitor site availability and track recent deployment revisions to identify if a specific code change triggered new regressions
- Team Audit — List registered team members and their roles to understand notification distribution and ownership for specific projects
The Honeybadger (Error Tracking) MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Honeybadger (Error Tracking) to Vercel AI SDK via MCP
Follow these steps to integrate the Honeybadger (Error Tracking) MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Honeybadger (Error Tracking) and passes them to the LLM
Why Use Vercel AI SDK with the Honeybadger (Error Tracking) MCP Server
Vercel AI SDK provides unique advantages when paired with Honeybadger (Error Tracking) through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Honeybadger (Error Tracking) integration everywhere
Built-in streaming UI primitives let you display Honeybadger (Error Tracking) tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Honeybadger (Error Tracking) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Honeybadger (Error Tracking) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Honeybadger (Error Tracking) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Honeybadger (Error Tracking) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Honeybadger (Error Tracking) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Honeybadger (Error Tracking) through natural language queries
Honeybadger (Error Tracking) MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Honeybadger (Error Tracking) to Vercel AI SDK via MCP:
get_fault
Get full details of a Honeybadger fault
get_notice
Get full details of a Honeybadger notice
get_project
Get full details of a Honeybadger project
list_deployments
List recent deployments registered in a Honeybadger project
list_faults
Returns class names, messages, environments, occurrence counts, and first/last noticed dates. List faults (error groups) for a Honeybadger project
list_members
List team members on a Honeybadger project
list_notices
List notices (individual error occurrences) for a Honeybadger fault
list_projects
Returns project names, IDs, tokens, language, environments, and fault/notice counts. List all projects in Honeybadger
list_sites
List uptime monitoring sites in a Honeybadger project
resolve_fault
Irreversible matrix state change. Resolve a Honeybadger fault
Example Prompts for Honeybadger (Error Tracking) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Honeybadger (Error Tracking) immediately.
"List all unresolved faults in my 'production-backend' project"
"Show me the details for fault ID 123456"
"List recent deployments for project ID 9876"
Troubleshooting Honeybadger (Error Tracking) MCP Server with Vercel AI SDK
Common issues when connecting Honeybadger (Error Tracking) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpHoneybadger (Error Tracking) + Vercel AI SDK FAQ
Common questions about integrating Honeybadger (Error Tracking) MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Honeybadger (Error Tracking) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Honeybadger (Error Tracking) to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
