H2O.ai MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect H2O.ai 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 H2O.ai, 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 H2O.ai MCP Server
Connect your H2O.ai instance to any AI agent and take full control of your machine learning lifecycle, automated data processing, and cluster monitoring through natural conversation.
The Vercel AI SDK gives every H2O.ai tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 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
- Data Frame Orchestration — List structured datasets securely loaded into H2O clusters and retrieve specific dimensional data mapping explicit frame columns natively
- Model Inventory Auditing — Iterate through tracked machine learning models previously generated inside your cloud instance to verify performance metrics and versions
- Inference Monitoring — Access detailed configuration blocks for active model architectures to verify deployment boundaries and parameters synchronously
- Training Job Oversight — Query timeline nodes tracking long-running tasks and model training jobs queued on the cluster to monitor execution progress
- Cloud Cluster Auditing — Ping root endpoints defining hardware architecture health and memory utilization within your H2O instances flawlessly
- MLOps Command Center — Verify available frames and models to orchestrate complex data science workflows and model evaluations using natural language
- Status Verification — Identify precise executing statuses of ongoing jobs to ensure your AI pipeline is operational and within resource limits securely
The H2O.ai MCP Server exposes 6 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 H2O.ai to Vercel AI SDK via MCP
Follow these steps to integrate the H2O.ai 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 6 tools from H2O.ai and passes them to the LLM
Why Use Vercel AI SDK with the H2O.ai MCP Server
Vercel AI SDK provides unique advantages when paired with H2O.ai 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 H2O.ai integration everywhere
Built-in streaming UI primitives let you display H2O.ai 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
H2O.ai + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the H2O.ai MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query H2O.ai in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate H2O.ai tools and return structured JSON responses to any frontend
Chatbots with tool use: embed H2O.ai capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with H2O.ai through natural language queries
H2O.ai MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect H2O.ai to Vercel AI SDK via MCP:
cloud_status
Get cloud status
get_frame
Get frame
get_model
Get model
list_frames
List frames
list_jobs
List jobs
list_models
List models
Example Prompts for H2O.ai in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with H2O.ai immediately.
"List all machine learning models in my H2O cluster"
"What is the current status of the H2O cloud cluster?"
"Show me the last 3 training jobs"
Troubleshooting H2O.ai MCP Server with Vercel AI SDK
Common issues when connecting H2O.ai to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpH2O.ai + Vercel AI SDK FAQ
Common questions about integrating H2O.ai 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 H2O.ai 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 H2O.ai to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.