Where do I find my UPYUN Operator details?

Log into your UPYUN console, click on 'Cloud Storage' -> 'Your Service/Bucket' -> 'Configuration' -> 'Operators'. From there you can copy the operator name and the generated password.

Does the AI see my files if I connect this?

The AI uses this MCP to only perform the standard API queries you allow it. Use an Operator with specific folder limits if you wish to restrict directory access.

UPYUN Developer Platform MCP Server for CrewAI 5 tools — connect in under 2 minutes

Name: UPYUN Developer Platform
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 5 Tools Framework

Connect your CrewAI agents to UPYUN Developer Platform through Vinkius, pass the Edge URL in the `mcps` parameter and every UPYUN Developer Platform 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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="UPYUN Developer Platform Specialist",
    goal="Help users interact with UPYUN Developer Platform effectively",
    backstory=(
        "You are an expert at leveraging UPYUN Developer Platform 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 UPYUN Developer Platform "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 5 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 UPYUN Developer Platform MCP Server

Integrate your AI with UPYUN (又拍云), one of the most prominent Cloud and CDN providers in the world. This MCP gives your agent direct file management access to your cloud buckets.

When paired with CrewAI, UPYUN Developer Platform becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call UPYUN Developer Platform 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

Cloud Storage Management — Automatically create, view, list, and delete files inside your UPYUN buckets without downloading their manual command line clients
CDN Artifact Uploads — Enable the LLM to directly write code logic or textual artifacts and deploy them live to your CDN domains instantly
Capacity Auditing — Fetch storage usage to monitor consumption on your buckets dynamically

The UPYUN Developer Platform MCP Server exposes 5 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 UPYUN Developer Platform to CrewAI via MCP

Follow these steps to integrate the UPYUN Developer Platform 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 5 tools from UPYUN Developer Platform

Why Use CrewAI with the UPYUN Developer Platform MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with UPYUN Developer Platform 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

UPYUN Developer Platform + CrewAI Use Cases

Practical scenarios where CrewAI combined with the UPYUN Developer Platform MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries UPYUN Developer Platform 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 UPYUN Developer Platform, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain UPYUN Developer Platform 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 UPYUN Developer Platform against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

UPYUN Developer Platform MCP Tools for CrewAI (5)

These 5 tools become available when you connect UPYUN Developer Platform to CrewAI via MCP:

create_text_file

Create and upload a text file directly to UPYUN

delete_file

Delete a file from UPYUN

get_file_info

Get metadata about an UPYUN file

get_service_usage

Get UPYUN bucket service usage

list_directory

g., "/" or "/images/") to list its contents. List files and folders in an UPYUN directory

Example Prompts for UPYUN Developer Platform in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with UPYUN Developer Platform immediately.

"List all files present in the root `/` directory of my Upyun bucket."

"Create a new text file at `/hello.txt` with the content 'Hello from MCP'."

Troubleshooting UPYUN Developer Platform MCP Server with CrewAI

Common issues when connecting UPYUN Developer Platform 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.

UPYUN Developer Platform + CrewAI FAQ

Common questions about integrating UPYUN Developer Platform 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.