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.

JD Cloud Infrastructure MCP Server for OpenAI Agents SDK 11 tools — connect in under 2 minutes

Name: JD Cloud Infrastructure
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 11 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect JD Cloud Infrastructure through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="JD Cloud Infrastructure Assistant",
            instructions=(
                "You help users interact with JD Cloud Infrastructure. "
                "You have access to 11 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from JD Cloud Infrastructure"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 OpenAI Agents SDK auto-discovers all 11 tools from JD Cloud Infrastructure through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries JD Cloud Infrastructure, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the JD Cloud Infrastructure MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 11 tools from JD Cloud Infrastructure

Why Use OpenAI Agents SDK with the JD Cloud Infrastructure MCP Server

OpenAI Agents SDK provides unique advantages when paired with JD Cloud Infrastructure through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

JD Cloud Infrastructure + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the JD Cloud Infrastructure MCP Server delivers measurable value.

Automated workflows: build agents that query JD Cloud Infrastructure, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries JD Cloud Infrastructure, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through JD Cloud Infrastructure tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query JD Cloud Infrastructure to resolve tickets, look up records, and update statuses without human intervention

JD Cloud Infrastructure MCP Tools for OpenAI Agents SDK (11)

These 11 tools become available when you connect JD Cloud Infrastructure to OpenAI Agents 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents 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 OpenAI Agents SDK

Common issues when connecting JD Cloud Infrastructure to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

JD Cloud Infrastructure + OpenAI Agents SDK FAQ

Common questions about integrating JD Cloud Infrastructure MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.