How to Use the JD Cloud / 京东云 MCP in CrewAI

Q: How do I configure a CrewAI agent with JD Cloud / 京东云?

Install crewai and crewaitools. You can pass your Vinkius server URL directly into the agent's mcps list. This MCP integration exposes tools like listvminstances to that specific agent instantly.

Q: Can I restrict which JD Cloud / 京东云 tools a CrewAI agent can use?

Yes, you can use MCPServerHTTP from the CrewAI library to apply a toolfilter. This lets you restrict a junior agent to only listossbuckets while keeping billing tools restricted to your finance agent.

Q: How does CrewAI guarantee the privacy of my JD Cloud / 京东云 IAM profiles?

Your IAM data fetched via getaccountprofile is processed in memory and never written to disk. Vinkius secures the transport layer with TLS 1.3, ensuring that credentials and user profiles remain hidden from external observers.

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Connect JD Cloud / 京东云 MCP to CrewAI

Create your Vinkius account to connect JD Cloud / 京东云 to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup JD Cloud / 京东云 with CrewAI

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Collaborative Infrastructure Audits

Stop relying on single-agent scripts that break when JD Cloud context windows fill up. CrewAI lets you deploy a team of agents where one uses `list_vm_instances` to map your compute footprint. A second agent analyzes the output of `get_vm_detail` to find underutilized nodes. They share memory and pass state back and forth to compile a clean optimization report.

Autonomous Security and Network Crews

Secure your JD Cloud network perimeter using autonomous CrewAI agents. A security agent runs `list_vpc_networks` to check security group rules and identify exposed public entry points. Meanwhile, a compliance agent calls `get_account_profile` to verify that only authorized IAM users have access to those networks. The entire process runs without human intervention.

Multi-Agent Billing Analysis with CrewAI

Manage your JD Cloud spend by letting CrewAI agents collaborate on cost data. An analyst agent pulls the latest figures with `get_billing_summary` to find cost spikes. It passes those findings to a storage specialist agent, which runs `list_oss_buckets` to cross-reference bucket sizes with your monthly bill. You get a detailed breakdown of where your money goes.

Setup guide

Set up JD Cloud / 京东云 MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke JD Cloud / 京东云 tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="JD Cloud / 京东云 Analyst",
    goal="Access and analyze JD Cloud / 京东云 data via MCP.",
    backstory="Expert analyst with direct JD Cloud / 京东云 access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent JD Cloud / 京东云 transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="JD Cloud / 京东云 Analyst",
        goal="Access and analyze JD Cloud / 京东云 data via MCP.",
        backstory="Expert analyst with direct JD Cloud / 京东云 access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent JD Cloud / 京东云 transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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 / 京东云. 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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Common questions about JD Cloud / 京东云 MCP in CrewAI

Install `crewai` and `crewai[tools]`. You can pass your Vinkius server URL directly into the agent's `mcps` list. This MCP integration exposes tools like `list_vm_instances` to that specific agent instantly.

Yes, you can use `MCPServerHTTP` from the CrewAI library to apply a `tool_filter`. This lets you restrict a junior agent to only `list_oss_buckets` while keeping billing tools restricted to your finance agent.

CrewAI agents use a shared memory system. When one agent runs `list_vpc_networks` via the MCP Server, the resulting network topology is stored in the shared context, allowing other agents in the crew to reference it without making redundant API calls.

CrewAI supports stdio, SSE, and Streamable HTTP. When connecting to your managed server on Vinkius, you will typically use the Streamable HTTP transport, which handles persistent agent connections smoothly.

Your IAM data fetched via `get_account_profile` is processed in memory and never written to disk. Vinkius secures the transport layer with TLS 1.3, ensuring that credentials and user profiles remain hidden from external observers.

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