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 Google ADK 11 tools — connect in under 2 minutes

Name: JD Cloud Infrastructure
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 11 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add JD Cloud Infrastructure as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

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

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="jd_cloud_infrastructure_agent",
    instruction=(
        "You help users interact with JD Cloud Infrastructure "
        "using 11 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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.

Google ADK natively supports JD Cloud Infrastructure as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 11 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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 Google ADK 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 Google ADK via MCP

Follow these steps to integrate the JD Cloud Infrastructure MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 11 tools from JD Cloud Infrastructure via MCP

Why Use Google ADK with the JD Cloud Infrastructure MCP Server

Google ADK provides unique advantages when paired with JD Cloud Infrastructure through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with JD Cloud Infrastructure

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine JD Cloud Infrastructure tools with BigQuery, Vertex AI, and Cloud Functions

JD Cloud Infrastructure + Google ADK Use Cases

Practical scenarios where Google ADK combined with the JD Cloud Infrastructure MCP Server delivers measurable value.

Enterprise data agents: ADK agents query JD Cloud Infrastructure and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine JD Cloud Infrastructure tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query JD Cloud Infrastructure regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including JD Cloud Infrastructure

JD Cloud Infrastructure MCP Tools for Google ADK (11)

These 11 tools become available when you connect JD Cloud Infrastructure to Google ADK 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 Google ADK

Ready-to-use prompts you can give your Google ADK 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 Google ADK

Common issues when connecting JD Cloud Infrastructure to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

JD Cloud Infrastructure + Google ADK FAQ

Common questions about integrating JD Cloud Infrastructure MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.