Honeycomb MCP Server for Vercel AI SDK 12 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Honeycomb through the 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 Honeycomb, 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 Honeycomb MCP Server
Connect your Honeycomb.io observability platform to any AI agent and take full control of your telemetry data, query specifications, and incident markers through natural conversation.
The Vercel AI SDK gives every Honeycomb tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 tools through the 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
- Dataset Oversight — List all event sources, retrieve detailed metadata, and monitor last access times for your datasets.
- Query Management — Define new query specifications and execute them to retrieve granular performance insights.
- Marker Automation — Create timeline annotations (e.g., for deployments or outages) to contextualize your data visualization.
- Schema Insights — List and inspect columns within specific datasets to understand your event structure.
- Team Collaboration — Access shared boards and retrieve information about your Honeycomb team configuration.
- Incident Analysis — Use AI to run complex queries and retrieve results for rapid troubleshooting and RCA.
The Honeycomb MCP Server exposes 12 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 Honeycomb to Vercel AI SDK via MCP
Follow these steps to integrate the Honeycomb 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 12 tools from Honeycomb and passes them to the LLM
Why Use Vercel AI SDK with the Honeycomb MCP Server
Vercel AI SDK provides unique advantages when paired with Honeycomb 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 Honeycomb integration everywhere
Built-in streaming UI primitives let you display Honeycomb 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
Honeycomb + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Honeycomb MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Honeycomb in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Honeycomb tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Honeycomb capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Honeycomb through natural language queries
Honeycomb MCP Tools for Vercel AI SDK (12)
These 12 tools become available when you connect Honeycomb to Vercel AI SDK via MCP:
create_marker
Pass details as a JSON string in "body_json" (requires message). Use "__all__" for team-wide markers. Create a new marker (e.g., deploy, maintenance) on a dataset timeline
create_query_specification
Pass the specification as a JSON string in "query_json". Returns a query ID for execution. Create a new query specification for a dataset
get_dataset_details
Get metadata for a specific dataset
get_query_result
Retrieve the results of an executed query
get_team_details
Retrieve information about the Honeycomb team
list_dataset_columns
List all columns (fields) defined in a specific dataset
list_datasets
Use this to find the "slug" required for markers and queries. List all datasets in your Honeycomb team
list_honeycomb_boards
List all boards (dashboards) shared with the team
list_markers
List markers (annotations) for a dataset
list_queries
List query specifications for a specific dataset
list_triggers
List triggers (alerts) defined for a dataset
run_query
Poll for results using "get_query_result" with the returned result ID. Execute a query specification and return a result ID
Example Prompts for Honeycomb in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Honeycomb immediately.
"List all datasets and find one related to 'payment-gateway'."
"Create a marker on all datasets: 'Deploy v2.4.0 started'."
"Execute query ID 'q_99283' for the 'main-api' dataset."
Troubleshooting Honeycomb MCP Server with Vercel AI SDK
Common issues when connecting Honeycomb to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpHoneycomb + Vercel AI SDK FAQ
Common questions about integrating Honeycomb 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 Honeycomb 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 Honeycomb to Vercel AI SDK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.