NVIDIA AI MCP Server for Vercel AI SDK 9 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect NVIDIA AI through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
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 NVIDIA 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 NVIDIA AI MCP Server
Connect NVIDIA AI to any AI agent and harness the power of GPU-accelerated foundation models — chat with Llama, generate embeddings, write code with CodeLlama, translate text, and perform complex reasoning through the NVIDIA API Catalog.
The Vercel AI SDK gives every NVIDIA AI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 9 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
- Chat with LLMs — Access Llama 3.1, Mistral, Nemotron, and more via chat completions
- Generate Embeddings — Create vector embeddings for search and clustering
- Code Generation — Write code from natural language prompts using CodeLlama
- Summarization — Condense long documents into concise summaries
- Translation — Neural translation between dozens of languages
- Text-to-SQL — Convert natural language questions into SQL queries
- Sentiment Analysis — Analyze the emotional tone of text
- Complex Reasoning — Ask questions to the 405B-parameter reasoning model
The NVIDIA AI MCP Server exposes 9 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 NVIDIA AI to Vercel AI SDK via MCP
Follow these steps to integrate the NVIDIA 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 9 tools from NVIDIA AI and passes them to the LLM
Why Use Vercel AI SDK with the NVIDIA AI MCP Server
Vercel AI SDK provides unique advantages when paired with NVIDIA 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 NVIDIA AI integration everywhere
Built-in streaming UI primitives let you display NVIDIA 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
NVIDIA AI + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the NVIDIA AI MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query NVIDIA AI in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate NVIDIA AI tools and return structured JSON responses to any frontend
Chatbots with tool use: embed NVIDIA AI capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with NVIDIA AI through natural language queries
NVIDIA AI MCP Tools for Vercel AI SDK (9)
These 9 tools become available when you connect NVIDIA AI to Vercel AI SDK via MCP:
analyze_sentiment
Analyze the sentiment of a text
ask_question
Optionally provide context for better answers. Ask a question to a powerful reasoning model (405B params)
chat_completion
Use "model" to specify which AI model (e.g., "meta/llama-3.1-70b-instruct", "mistralai/mistral-large"). Messages should be in OpenAI format: [{role: "user", content: "..."}]. Chat with an NVIDIA AI model (Llama, Mistral, etc)
generate_code
Specify language if needed. Generate code from a natural language prompt
get_embeddings
Model: "nvidia/nv-embed-v1". Generate vector embeddings from text
list_models
List all available AI models on the NVIDIA API Catalog
summarize_text
Summarize long text into a concise version
text_to_sql
Convert natural language to SQL query
translate_text
Translate text to another language
Example Prompts for NVIDIA AI in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with NVIDIA AI immediately.
"Generate Python code for a REST API with FastAPI."
"Translate 'Hello, how are you?' to Japanese."
"Summarize: The quarterly report shows revenue grew 15% YoY..."
Troubleshooting NVIDIA AI MCP Server with Vercel AI SDK
Common issues when connecting NVIDIA AI to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpNVIDIA AI + Vercel AI SDK FAQ
Common questions about integrating NVIDIA 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 NVIDIA 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 NVIDIA AI to Vercel AI SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.