JD Cloud Infrastructure 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 JD Cloud Infrastructure through 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 JD Cloud Infrastructure, 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 JD Cloud Infrastructure MCP Server
Connect your AI agents directly to JD Cloud (京东云), the enterprise cloud infrastructure backing one of the world's largest e-commerce and supply chain platforms. This MCP provides 11 power tools spanning the full infrastructure lifecycle.
The Vercel AI SDK gives every JD Cloud Infrastructure 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
- VM Lifecycle Management — List, inspect, start, stop, and reboot virtual machines through natural language
- Storage Operations — Enumerate and inspect cloud disks and Object Storage buckets
- Network Oversight — Query Elastic IP allocations and their association status
- Database Administration — List RDS instances with engine versions and connection status
- Performance Monitoring — Pull time-series CPU, network, and disk metrics for any resource
The JD Cloud Infrastructure 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 JD Cloud Infrastructure to Vercel AI SDK via MCP
Follow these steps to integrate the JD Cloud Infrastructure 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 JD Cloud Infrastructure and passes them to the LLM
Why Use Vercel AI SDK with the JD Cloud Infrastructure MCP Server
Vercel AI SDK provides unique advantages when paired with JD Cloud Infrastructure 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 JD Cloud Infrastructure integration everywhere
Built-in streaming UI primitives let you display JD Cloud Infrastructure 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
JD Cloud Infrastructure + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the JD Cloud Infrastructure MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query JD Cloud Infrastructure in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate JD Cloud Infrastructure tools and return structured JSON responses to any frontend
Chatbots with tool use: embed JD Cloud Infrastructure capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with JD Cloud Infrastructure through natural language queries
JD Cloud Infrastructure MCP Tools for Vercel AI SDK (11)
These 11 tools become available when you connect JD Cloud Infrastructure to Vercel AI SDK via MCP:
describe_cloud_disk
Get detailed information about a specific cloud disk
describe_metric_data
Query monitoring metric data for a cloud resource
describe_vm_instance
Get detailed information about a specific VM instance
list_cloud_disks
List all cloud disk volumes in your region
list_elastic_ips
List all Elastic IP addresses in your region
list_oss_buckets
List all Object Storage Service buckets
list_rds_instances
List all RDS database instances in your region
list_vm_instances
List all virtual machine instances in your JD Cloud region
reboot_vm_instance
Reboot a VM instance
start_vm_instance
Start a stopped VM instance
stop_vm_instance
Stop a running VM instance
Example Prompts for JD Cloud Infrastructure in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with JD Cloud Infrastructure immediately.
"List all my running virtual machines on JD Cloud."
"Show me the CPU usage for instance i-abc123 over the last hour."
Troubleshooting JD Cloud Infrastructure MCP Server with Vercel AI SDK
Common issues when connecting JD Cloud Infrastructure to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpJD Cloud Infrastructure + Vercel AI SDK FAQ
Common questions about integrating JD Cloud Infrastructure 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 JD Cloud Infrastructure 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 JD Cloud Infrastructure to Vercel AI SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.