RunPod MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect RunPod 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 RunPod, 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 RunPod MCP Server
Connect your AI directly to RunPod, the leading cloud infrastructure provider for on-demand GPU computing and serverless execution. Empower your conversational agent to act as a highly proficient DevOp engineer, managing advanced computational workloads, exploring deployment options, and spinning up new hardware instances.
The Vercel AI SDK gives every RunPod tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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
- Manage Pods On-Demand — Effortlessly identify running and paused GPU machines across your cloud account (
list_pods,get_pod). Halt specific billable instances to control costs securely (stop_pod). - Provision GPU Workloads — Find verified templates or specific GPU architectures ready for deployment (
list_templates,list_gpu_types), and create entirely new hardware nodes immediately directly from chat (create_pod). - Audit Serverless Environments — Review all registered endpoints routing your containerized inference applications (
list_endpoints).
The RunPod MCP Server exposes 7 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 RunPod to Vercel AI SDK via MCP
Follow these steps to integrate the RunPod 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 7 tools from RunPod and passes them to the LLM
Why Use Vercel AI SDK with the RunPod MCP Server
Vercel AI SDK provides unique advantages when paired with RunPod 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 RunPod integration everywhere
Built-in streaming UI primitives let you display RunPod 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
RunPod + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the RunPod MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query RunPod in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate RunPod tools and return structured JSON responses to any frontend
Chatbots with tool use: embed RunPod capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with RunPod through natural language queries
RunPod MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect RunPod to Vercel AI SDK via MCP:
create_pod
Specify name, GPU type, and Docker image. Creates a new GPU pod
get_pod
Retrieves details for a specific GPU pod
list_endpoints
Lists all serverless endpoints
list_gpu_types
Lists available GPU hardware types
list_pods
Lists all GPU pods in the account
list_templates
Lists saved pod templates
stop_pod
Stops a running GPU pod
Example Prompts for RunPod in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with RunPod immediately.
"Show me our stopped GPU pods."
"Check what GPU templates are available to deploy a new Llama-3 inference instance."
"Pause pod with ID 'pod_xyz_980' immediately to prevent recurring costs throughout the evening."
Troubleshooting RunPod MCP Server with Vercel AI SDK
Common issues when connecting RunPod to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpRunPod + Vercel AI SDK FAQ
Common questions about integrating RunPod 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 RunPod 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 RunPod to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.