Amazon S3 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 Amazon S3 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 Amazon S3, 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 Amazon S3 MCP Server
Connect your Amazon S3 environment to your AI agent to unlock professional cloud storage orchestration. From creating and auditing buckets to managing individual objects and their metadata, your agent handles your AWS data storage through natural conversation.
The Vercel AI SDK gives every Amazon S3 tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 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
- Bucket Orchestration — List your S3 buckets, create new ones, and retrieve their location or policy configurations
- Object Management — List objects within a specific bucket, including their size and last modified timestamps
- Data Ingestion — Upload objects directly to S3 or delete unwanted files to maintain your storage hygiene
- Metadata Auditing — Retrieve technical metadata (headers, content type, size) for specific objects without downloading them
- Security Oversight — Audit bucket ACLs and policies to ensure your cloud storage meets compliance requirements
The Amazon S3 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 Amazon S3 to Vercel AI SDK via MCP
Follow these steps to integrate the Amazon S3 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 Amazon S3 and passes them to the LLM
Why Use Vercel AI SDK with the Amazon S3 MCP Server
Vercel AI SDK provides unique advantages when paired with Amazon S3 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 Amazon S3 integration everywhere
Built-in streaming UI primitives let you display Amazon S3 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
Amazon S3 + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Amazon S3 MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Amazon S3 in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Amazon S3 tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Amazon S3 capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Amazon S3 through natural language queries
Amazon S3 MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Amazon S3 to Vercel AI SDK via MCP:
create_bucket
Create an S3 bucket
delete_bucket
Delete an S3 bucket
delete_object
Delete an object
get_bucket_acl
Get bucket ACL
get_bucket_policy
Get bucket policy
get_object_data
Get object content
get_object_metadata
Get object metadata
list_buckets
List S3 buckets
list_objects
Can be filtered by prefix. List objects in bucket
put_object
Upload an object
Example Prompts for Amazon S3 in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Amazon S3 immediately.
"List all S3 buckets in my account."
"Show the top 10 objects in bucket 'data-lake-raw' starting with prefix '2026/03/'."
"Get the bucket policy for 'website-images-eu'."
Troubleshooting Amazon S3 MCP Server with Vercel AI SDK
Common issues when connecting Amazon S3 to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpAmazon S3 + Vercel AI SDK FAQ
Common questions about integrating Amazon S3 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 Amazon S3 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 Amazon S3 to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.