How to Use the Aliyun OSS / 阿里云对象存储 MCP in Vercel AI SDK

Q: How do I list files from Aliyun OSS / 阿里云对象存储 in Vercel AI SDK?

You call the listobjects tool through the MCP client instance. The results return as an array that you can map directly to your interface.

Q: Can Vercel AI SDK upload files to Aliyun OSS / 阿里云对象存储?

Yes, you use the uploadobject tool. Pass your text content and target path to the function, and the server handles the transfer.

Stream Aliyun OSS / 阿里云对象存储 file data straight into your Vercel AI SDK frontends for real-time UI updates.

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Connect Aliyun OSS / 阿里云对象存储 MCP to Vercel AI SDK

Create your Vinkius account to connect Aliyun OSS / 阿里云对象存储 to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Aliyun OSS / 阿里云对象存储 with Vercel AI SDK

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Read and write buckets with Vercel AI SDK

Use `list_objects` to pull file structures and `download_object_text` to feed raw data into your React components. Your users see the content populate instantly without waiting for backend roundtrips. Everything happens over HTTP transport. You get clean text output directly from your storage buckets into the browser.

Manage storage metadata in Next.js

Run `get_object_metadata` to check file sizes or timestamps before triggering logic. This keeps your application state in sync with your cloud storage. Call `get_bucket_info` to verify region settings within your Edge Functions. It gives your code the context it needs to handle assets correctly.

Upload and modify files via MCP Server

Trigger `upload_object` to save user-generated text directly to your bucket. It handles files up to 5GB per request. Use `copy_object` and `delete_object` to reorganize your cloud storage programmatically. This MCP Server makes file maintenance a simple function call in your code.

Setup guide

Set up Aliyun OSS / 阿里云对象存储 MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Aliyun OSS / 阿里云对象存储 tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Aliyun OSS / 阿里云对象存储 transactions",
});

console.log(text);
await mcpClient.close();

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Aliyun OSS / 阿里云对象存储. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Aliyun OSS / 阿里云对象存储 MCP in Vercel AI SDK

You call the `list_objects` tool through the MCP client instance. The results return as an array that you can map directly to your interface.

Yes, you use the `upload_object` tool. Pass your text content and target path to the function, and the server handles the transfer.

It is fully compatible. You just need to initialize the client with the provided endpoint and your tools become available to your agents.

The server supports uploads up to 5GB. For text files, use the specific download tools to stream content into your application memory.

This server only touches the specific bucket keys you authorize. It operates inside a V8 sandbox, ensuring your credentials never leak to external processes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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