UPYUN Developer Platform MCP. Manage assets, deploy code, and audit storage capacity.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
UPYUN Developer Platform MCP Server gives your AI agent direct API access to UPYUN's CDN and cloud storage buckets. You can manage files, list directories, create new assets, and check service capacity without using any command-line tools or local SDKs.
It lets your agent interact with your entire file system like a native developer would.
What your AI agents can do
Create text file
Creates and uploads a plain text file to UPYUN's cloud storage bucket.
Delete file
Deletes any specified file from your UPYUN cloud buckets.
Get file info
Retrieves metadata (like size or modification date) for a specific UPYUN file path.
The agent lists all files and folders within a specified UPYUN directory path.
The agent writes and uploads new text files directly into your UPYUN bucket.
The agent removes specified files from any location within the UPYUN bucket structure.
The agent retrieves specific details, like size and last modified date, for a single file.
The agent fetches usage statistics to report on how much storage you've consumed in your UPYUN bucket.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
UPYUN Developer Platform: 5 Tools for Cloud Operations
Use these five tools to allow your agent full control over file system actions—from creating new assets to auditing service usage across UPYUN buckets.
019d8496create text file
Creates and uploads a plain text file to UPYUN's cloud storage bucket.
019d8496delete file
Deletes any specified file from your UPYUN cloud buckets.
019d8496get file info
Retrieves metadata (like size or modification date) for a specific UPYUN file path.
019d8496get service usage
Fetches and reports the overall storage usage metrics for your entire UPYUN bucket service.
019d8496list directory
Lists all files and subfolders contained within a specified UPYUN directory path.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with UPYUN Developer Platform, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Yo, this UPYUN Developer Platform MCP Server hooks up your AI agent straight to UPYUN's CDN and cloud storage buckets. You don't need any command-line crap or local SDKs; your agent can treat your whole file system like it's running on a native dev machine. It gives you direct API access, so you can manage files, build assets, list directories, delete stuff, and check service capacity—all without leaving your AI client.
Managing Your Files
Your agent handles all the heavy lifting when it comes to file operations. You'll use list_directory to pull a full manifest of every file and subfolder within any specified UPYUN directory path, letting you see exactly what's hanging out there. Need to drop new content? Just call create_text_file, and your agent uploads a plain text file right into the cloud storage bucket for you.
When you’re done with something, remember that delete_file lets your agent wipe any specified file from anywhere in the UPYUN bucket structure.
Getting File Details and Usage Stats
The server gives you visibility on what's going on under the hood. You can check the specifics of a single file using get_file_info; this retrieves metadata like its size or when it was last modified. And if you need to know how much storage space you’ve burned through, just run get_service_usage.
That pulls and reports the overall usage metrics for your entire UPYUN bucket service.
How It Works
It's straightforward: Your agent connects to this server on Vinkius. When it needs to perform any of these actions—like listing a folder or creating a file—it sends the request through the MCP, and we handle the complex API auth behind the scenes. This keeps your credentials safe while giving you that full-blast control over your assets.
How UPYUN Developer Platform MCP Works
- 1 Subscribe to the UPYUN Developer Platform server.
- 2 Retrieve an Operator Name and Password from your UPYUN API access page.
- 3 Inject those credentials into your agent. The MCP handles secure authentication, letting your AI client interact with the cloud.
The bottom line is: you provide the keys, and the server lets your AI agent use them to manage files and check stats in your UPYUN buckets.
Who Is UPYUN Developer Platform MCP For?
This is for DevOps engineers who are sick of writing boilerplate deployment scripts. It’s also useful for frontend devs prototyping sites or content admins needing quick asset checks without logging into a dashboard. If your job involves managing assets across cloud storage, this saves hours.
Automates static site generation and deployments by pushing file changes directly to UPYUN instances using tools like create_text_file.
Prototyping web apps without writing complex deployment scripts; they use the agent to deploy files instantly via the MCP.
Quickly checks what assets are in specific directories—like verifying if a logo file exists—using list_directory via natural language prompts.
What Changes When You Connect
- Stop writing deployment scripts. Your agent can use
create_text_fileto deploy new static content or updated HTML files directly to your CDN domains. - Need a quick asset check? Use the
list_directorytool to see everything in a bucket's root path just by asking, avoiding manual navigation through a web console. - Track costs and capacity easily. The
get_service_usagetool gives you real-time storage metrics so you know exactly when you hit your consumption limits. - Need to clean up old assets? Use
delete_filewith natural language prompts to remove junk files without needing to manually specify every single file path. - Get details on any asset instantly. Run
get_file_infoto check a file's size or last modified date before relying on it for production code.
Real-World Use Cases
A new page needs assets uploaded and checked.
The content team writes a new landing page. They ask their agent to first run list_directory to check if the 'images' folder exists. If it does, they ask the agent to use create_text_file to upload the new CSS file, and finally, they use get_file_info on that new file to confirm its size.
The site is running low on space.
A DevOps engineer notices potential billing issues. They prompt their agent with a request for 'current storage usage.' The agent immediately calls get_service_usage and reports the bucket's remaining capacity, preventing overspending.
Old development assets need to be purged.
A developer finishes a project branch. Instead of manually logging in and deleting files, they instruct their agent: 'Delete all temporary JS files from the /temp/ directory.' The agent executes delete_file across the whole group.
Deploying a quick patch requires a new file.
The frontend team needs to test an emergency fix. They ask their agent to create a placeholder file: 'Create /hotfix.html with content
Test
.' The agent executescreate_text_file, and the changes are live on the CDN. The Tradeoffs
Assuming listing shows everything.
User asks: 'Show me all assets in my bucket.' They assume they get file contents, but list_directory only gives them paths and folder names. This leads to follow-up prompts that waste time.
→
Trying to delete a directory.
delete_file is for individual files; it won't work on folders, even if you give it the path to a full folder. You have to target every file inside manually or via scripting.
→
Over-relying only on `get_file_info`.
If you only run get_file_info repeatedly, you get metadata but never see the full structure. You'll end up calling it dozens of times when a single list_directory call would have given you the map first.
→
Ignoring service limits.
Deploying large numbers of files without checking capacity leads to rate limiting or billing surprises. Always check with get_service_usage first.
→
When It Fits, When It Doesn't
Use this server if your workflow requires managing physical assets (files, folders) and tracking usage metrics on a cloud CDN like UPYUN. Specifically, use it when you need an AI agent to execute file system primitives: listing (list_directory), creating (create_text_file), deleting (delete_file), or checking status (get_file_info).
Don't use this if your problem is purely about data transformation (e.g., converting JSON to XML) or complex business logic that doesn't touch the file system itself. For usage reporting, get_service_usage is specific; don’t try to get billing reports via list_directory. Stick to these boundaries for predictable results.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by UPYUN. 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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 5 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manually managing cloud assets feels like running a dozen different CLI commands.
Today, updating an asset means logging into the web console or setting up a local build script. You have to click through folders, copy out file paths, and then run separate delete or upload commands for every single item. It’s slow, error-prone, and you're always worried about deleting the wrong thing.
With this MCP server, your agent handles it all in natural language. Need to list everything? Just ask. Need to deploy a patch? The agent runs `create_text_file` and gets the asset live. You just get the result—the change is made.
The UPYUN Developer Platform MCP Server: File & Bucket Operations
Forget writing complex Python scripts that handle authentication, file paths, and error checking. You never have to worry about the HMAC-SHA1 header generation again.
The agent manages all those low-level details for you. It’s just clean access: you tell it to list a directory, and it returns the contents. Done.
Common Questions About UPYUN Developer Platform MCP
How do I check how much storage I'm using with `get_service_usage`? +
get_service_usage reports your current consumption against your total bucket limit. It gives a summary metric, telling you exactly what percentage of your allotted space is used.
Can I use `list_directory` to see files inside subfolders? +
Yes, list_directory reads the contents of a specified path. You can point it at a folder like /images/assets/ to list everything within that subdirectory.
What should I use if I need to add a new asset? Should I use `create_text_file`? +
Yep, create_text_file is the tool for uploading assets. You give it the file path and the content string, and it handles writing the text data directly to your bucket.
Is there a specific way to check if a file exists using `get_file_info`? +
Running get_file_info on a specific path will confirm existence. If the file isn't found, the tool returns an error, which your agent uses to let you know it's missing.
What credentials do I need to use tools like `list_directory`? +
You need an Operator Name and Password from your UPYUN API access page. Plug these credentials into your agent, and the MCP handles the complex authorization process for you.
How does the system secure file operations when I use `create_text_file`? +
The MCP abstracts away the legacy HMAC-SHA1 Authorization header generation. You don't have to worry about generating these headers; your agent handles it securely.
If I try to delete a file that doesn’t exist using `delete_file`, what happens? +
The system reports the failure directly. The agent will tell you if the file path is invalid or if the deletion attempt failed, keeping your workflow clear.
Does `list_directory` handle large buckets efficiently? +
Yes. It lists files and folders in an UPYUN directory structure. The tool lets you check contents without needing to download manual command line clients or process massive data dumps.
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Amazon Redshift
Equip your AI to directly query, analyze, and manage your petabyte-scale data warehouse via the serverless AWS Redshift Data API.
Better Stack
Automate incident management via Better Stack — monitor uptime, manage incidents, and control on-call schedules securely from your AI agent.
Mux
Manage video assets and live streams via Mux — create assets and track performance directly from your AI agent.
You might also like
Ometria Email Events
Track and analyze email engagement events via Ometria — monitor opens, clicks, and bounces directly from your AI agent.
Qualified.io
Automate technical hiring and coding assessments — manage assessments, invite candidates, and track test results directly from your AI agent.
QStash (Serverless Message Queue)
Manage serverless messaging, task scheduling, and webhooks via Upstash QStash — publish messages, manage queues, and handle DLQs directly.