How do I check the real-time health of a specific computing node?

Use the `get_node` tool with the corresponding `node_id`. It will return real-time metrics including CPU, GPU, and Memory usage, as well as the current online status.

Can I deploy a new computing task using the agent?

Yes. Use the `create_task` tool. You will need to provide the `image_id` and the `cluster_id` where you want to deploy the task. You can also optionaly give the task a name.

Is it possible to remotely reboot a node through the chat?

Yes, using the `send_node_command` tool. You just need the `node_id` and specify 'reboot' as the command. This allows for rapid remote maintenance without manual intervention.

Shunwang Tech MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Shunwang Tech
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Shunwang Tech through Vinkius, pass the Edge URL in the `mcps` parameter and every Shunwang Tech tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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 crewai import Agent, Task, Crew

agent = Agent(
    role="Shunwang Tech Specialist",
    goal="Help users interact with Shunwang Tech effectively",
    backstory=(
        "You are an expert at leveraging Shunwang Tech tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Shunwang Tech "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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* 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 Shunwang Tech MCP Server

Empower your AI agent to orchestrate your edge computing infrastructure with Shunwang Tech, the dominant platform for PC Bang (Internet Cafe) management and distributed GPU resources in China. By connecting Shunwang to your agent, you transform complex resource scheduling and node monitoring into a natural conversation. Your agent can instantly list computing nodes, deploy new tasks to specific clusters, audit resource usage, and even send remote management commands without you ever touching a technical dashboard. Whether you are managing an AI inference network or a large-scale gaming infrastructure, your agent acts as a real-time infrastructure manager, ensuring your edge resources are always optimized and responsive.

When paired with CrewAI, Shunwang Tech becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Shunwang Tech tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Node Monitoring — List all computing nodes in your network, check real-time metrics (CPU, GPU, RAM), and audit their health status.
Task Scheduling — Create and deploy new computing tasks, stop running processes, and manage task lifecycles across your clusters.
Resource Optimization — Audit overall GPU specifications and resource usage summaries to optimize your edge-cloud synergy.
Cluster Management — Browse available computing clusters and organize your distributed infrastructure effectively.
Remote Operations — Send management commands like reboot or shutdown to specific nodes directly through the chat interface.

The Shunwang Tech MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI 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 Shunwang Tech to CrewAI via MCP

Follow these steps to integrate the Shunwang Tech MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Shunwang Tech

Why Use CrewAI with the Shunwang Tech MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Shunwang Tech through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Shunwang Tech + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Shunwang Tech MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Shunwang Tech for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Shunwang Tech, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Shunwang Tech tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Shunwang Tech against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Shunwang Tech MCP Tools for CrewAI (10)

These 10 tools become available when you connect Shunwang Tech to CrewAI via MCP:

create_task

Create a new computing task

get_gpu_specs

Get GPU specifications

get_node

Get node details

get_resource_usage

Get resource usage summary

list_clusters

List computing clusters

list_images

List available system images

list_nodes

List all computing nodes

list_tasks

List computing tasks

send_node_command

Send command to node

stop_task

Stop a computing task

Example Prompts for Shunwang Tech in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Shunwang Tech immediately.

"List all active computing nodes in my Shunwang network."

"Deploy a new task to cluster 'Huzhou-Edge-01' using image 'ai-inference-v2'."

"What is the current GPU resource usage across my entire Shunwang infrastructure?"

Troubleshooting Shunwang Tech MCP Server with CrewAI

Common issues when connecting Shunwang Tech to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Shunwang Tech + CrewAI FAQ

Common questions about integrating Shunwang Tech MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.