Vinkius
JD Cloud Infrastructure

JD Cloud Infrastructure MCP for AI. Manage VMs, disks, and databases in conversation.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

JD Cloud Infrastructure MCP on Cursor AI Code EditorJD Cloud Infrastructure MCP on Claude Desktop AppJD Cloud Infrastructure MCP on OpenAI Agents SDKJD Cloud Infrastructure MCP on Visual Studio CodeJD Cloud Infrastructure MCP on GitHub Copilot AI AgentJD Cloud Infrastructure MCP on Google Gemini AIJD Cloud Infrastructure MCP on Lovable AI DevelopmentJD Cloud Infrastructure MCP on Mistral AI AgentsJD Cloud Infrastructure MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

JD Cloud Infrastructure MCP connects your AI agent directly to JD Cloud's full suite of operations tools. You can manage VMs, disks, and databases from a single chat interface.

List instances, start/stop machines, monitor CPU usage, and check Object Storage buckets without leaving your development environment.

What your AI can do

Describe cloud disk

Gets detailed info on a specific cloud disk volume.

Describe vm instance

Retrieves detailed information about a specific virtual machine instance.

Describe metric data

Pulls monitoring metric data for any given cloud resource.

+ 8 more capabilities included
Manage VM State

You can list all virtual machines and send commands to start, stop, or reboot individual instances.

Monitor Resource Health

Query time-series data for CPU usage, network traffic, and disk performance on any resource.

Inventory Storage Resources

Get full listings of cloud disks and Object Storage Service buckets in your region.

Query Network Assets

List all Elastic IP allocations and confirm their current association status.

Included with Plan

Waiting for input…

AI Agent

JD Cloud Infrastructure: 11 Tools

Use these tools to query resource metrics, list all cloud components, and execute state changes across JD Cloud resources.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using JD Cloud Infrastructure on Vinkius

Describe Cloud Disk

Gets detailed info on a specific cloud disk volume.

Describe Vm Instance

Retrieves detailed information about a specific virtual machine instance.

Describe Metric Data

Pulls monitoring metric data for any given cloud resource.

List Oss Buckets

Gives a list of all Object Storage Service buckets.

List Cloud Disks

Provides an inventory of all cloud disk volumes in your region.

List Elastic Ips

Lists every Elastic IP address allocated to your account.

List Vm Instances

Lists all virtual machine instances currently running or stopped in the JD Cloud area.

List Rds Instances

Shows an inventory of all managed database (RDS) instances in your region.

Reboot Vm Instance

Forces a reboot cycle on an existing VM instance.

Start Vm Instance

Starts up a virtual machine that is currently stopped.

Stop Vm Instance

Shuts down a running VM instance to save costs or for maintenance.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The JD Cloud Infrastructure integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on every call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with JD Cloud Infrastructure, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,100+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Every connection is secured and compliant automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
JD Cloud Infrastructure MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by JD Cloud. 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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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 11 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

The Pain Point: Jumping Between Dashboards

Right now, diagnosing a cloud issue is a chore. You start on the main dashboard, find an alert about high CPU usage on VM-XYZ. Then you copy that ID and paste it into the Monitoring console to check metrics. If the disk is suspect, you have to open another tab just for disks, get the volume ID, and then cross-reference everything manually.

With this MCP, your agent does all of that work in one go. You ask: 'Why is VM-XYZ slow?' It automatically checks the CPU metrics using `describe_metric_data`, verifies the disk health with `describe_cloud_disk` if needed, and even tells you which resources are connected. The entire process happens without you leaving your chat window.

JD Cloud Infrastructure MCP: Full Control Over Resources

You no longer have to manually run a list command, grab an ID, and then feed it into another service. Instead, you simply ask the agent to 'List all active VMs and their associated disks.' The response is clean, comprehensive, and ready for action.

It’s about control—control over every state change, from stopping a machine with `stop_vm_instance` to getting full inventory via `list_rds_instances`. You run the operation, you get the status. Period.

What your AI can actually do with this

Managing cloud infrastructure usually means clicking through half a dozen different dashboards. You’re looking at VM status in one tab, disk metrics in another, and networking logs somewhere else. This MCP changes that. It gives your AI agent direct access to the core control plane for JD Cloud—the enterprise backbone running massive e-commerce operations.

Through this connection, you can query resource states, check performance graphs, and perform lifecycle actions using natural conversation. Whether it’s checking if a virtual machine needs a reboot or listing all available Object Storage buckets, your agent handles the API calls instantly. You get to skip the console hopping entirely.

Since Vinkius hosts this MCP, your agent connects once and gains access to JD Cloud's full operational toolkit, right alongside thousands of other services. It’s about getting immediate answers and executing changes without ever touching a cloud provider dashboard.

Built · Hosted · Managed by Vinkius JD Cloud Infrastructure MCP - Manage VMs & Databases
Server ID 019d844a-a417-714f-b904-e9bea6a4b9e1
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I check CPU usage using describe_metric_data? +

You pass the resource ID and specify the metric type (e.g., cpu.util). The agent returns time-series data, showing averages and peaks over the requested period.

What is the difference between stop_vm_instance and list_vm_instances? +

list_vm_instances just shows you what's there. stop_vm_instance actively changes the state, shutting down a running machine.

Can I use describe_cloud_disk to find out which VM it belongs to? +

The function gives detailed information about the disk itself (size, type). You must cross-reference that output with describe_vm_instance to confirm attachment.

Do I need to manually manage my access keys for list_elastic_ips? +

No. The MCP handles the complex authentication and signature generation using your provided Access Key and Secret Key automatically, so you just talk to it.

When I use `start_vm_instance` or `stop_vm_instance`, how do I handle common failure codes? +

The MCP returns the specific cloud error code and message. If a state change fails, check the detailed logs using describe_vm_instance; this pinpoints whether it's an invalid resource ID or a permission issue.

Do I hit rate limits when repeatedly calling `list_oss_buckets`? +

Yes, API rate limiting applies. While the MCP manages some retries automatically, making too many calls in quick succession can fail. For high-volume checks, consider batching your requests.

If my agent runs `describe_rds_instances` and doesn't see a database, what permissions am I missing? +

You need read access on the specific RDS resource group. The visibility of any resource is strictly tied to the IAM keys you provide; the AI client can only report what your credentials allow it to see.

Can I filter results when calling `list_vm_instances` by tags or criteria? +

Yes, you pass filters as arguments. To narrow down the scope of virtual machines, include specific tag keys and values in your request to get a highly targeted list.

Is the JDCLOUD2-HMAC-SHA256 signing handled automatically? +

Yes. The MCP engine locally derives signing keys through HMAC chains (date → region → service → jdcloud2_request), constructs canonical requests, and injects the Authorization header transparently. Your AI never handles raw crypto.

Built & Managed by Vinkius 30s setup 11 tools

We've already built the connector for JD Cloud Infrastructure. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 11 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
+ other MCP clients

Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.

Zero hosting required Full MCP catalog included Enterprise-grade security Auto-updated by Vinkius

Built, hosted, and secured by Vinkius. You just connect and go.