Qiniu Cloud MCP Server for Vercel AI SDK 11 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Qiniu Cloud 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 Qiniu Cloud, 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 Qiniu Cloud MCP Server
Connect your AI agents to Qiniu Cloud (七牛云), the leading enterprise cloud storage and content delivery network in China. This MCP provides 10 tools to manage the full lifecycle of your cloud assets, from bucket orchestration and file manipulation to CDN cache refreshment and global traffic monitoring.
The Vercel AI SDK gives every Qiniu Cloud tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 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
- Storage Orchestration — List buckets and manage file lifecycles, including deletions and bulk operations
- File Management — Retrieve granular metadata for stored assets and generate download URLs programmatically
- CDN Optimization — Refresh cache and prefetch content to ensure high-performance delivery across the network
- Usage Analytics — Monitor bandwidth consumption and storage quotas directly through natural conversation
The Qiniu Cloud MCP Server exposes 11 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 Qiniu Cloud to Vercel AI SDK via MCP
Follow these steps to integrate the Qiniu Cloud 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 11 tools from Qiniu Cloud and passes them to the LLM
Why Use Vercel AI SDK with the Qiniu Cloud MCP Server
Vercel AI SDK provides unique advantages when paired with Qiniu Cloud 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 Qiniu Cloud integration everywhere
Built-in streaming UI primitives let you display Qiniu Cloud 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
Qiniu Cloud + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Qiniu Cloud MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Qiniu Cloud in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Qiniu Cloud tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Qiniu Cloud capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Qiniu Cloud through natural language queries
Qiniu Cloud MCP Tools for Vercel AI SDK (11)
These 11 tools become available when you connect Qiniu Cloud to Vercel AI SDK via MCP:
delete_file
Delete a file from a bucket
get_account_info
Retrieve Qiniu account profile
get_bucket_domains
Get domains associated with a specific bucket
get_cdn_bandwidth
Get CDN bandwidth statistics
get_file_stat
Get metadata for a specific file
get_pfop_status
Check the status of a persistent processing task
get_sms_stats
Get SMS sending statistics
list_buckets
List all storage buckets in your Qiniu account
list_files
List files within a bucket
persistent_file_op
Trigger persistent file processing (transcoding, etc.)
refresh_cdn_urls
Refresh CDN cache for specific URLs
Example Prompts for Qiniu Cloud in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Qiniu Cloud immediately.
"List all storage buckets in my Qiniu account."
"Get the file status for 'logo.png' in bucket 'media-assets'."
"Refresh the CDN cache for 'https://cdn.example.com/styles.css'."
Troubleshooting Qiniu Cloud MCP Server with Vercel AI SDK
Common issues when connecting Qiniu Cloud to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpQiniu Cloud + Vercel AI SDK FAQ
Common questions about integrating Qiniu Cloud 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 Qiniu Cloud 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 Qiniu Cloud to Vercel AI SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.