Vinkius

Paperspace MCP. See GPU status, deployments, and compute resources instantly.

Paperspace MCP gives your AI client visibility into complex cloud machine learning environments. Use it to list active compute instances, trace deployed services, inspect Jupyter notebooks, and map user accounts across deep learning infrastructure. It's essential for anyone needing real-time status on GPU resources.

Paperspace MCP is compatible with Claude Claude
Paperspace MCP is compatible with ChatGPT ChatGPT
Paperspace MCP is compatible with Cursor Cursor
Paperspace MCP is compatible with Gemini Gemini
Paperspace MCP is compatible with Windsurf Windsurf
Paperspace MCP is compatible with VS Code VS Code
Paperspace MCP is compatible with JetBrains JetBrains
Paperspace MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Check active compute resources

Identify all provisioned machine cores, checking their current status and resource limits.

Audit deployed services

Retrieve logs and statuses for specific cloud deployment targets to ensure containers are available.

Inspect ML project boundaries

List structured project groupings, verifying team limits and GPU unit assignments across the platform.

Query notebook usage

Find details on Jupyter notebooks by inspecting deep internal arrays that govern AI workloads.

Verify user identity access

Identify all linked account identities and associated billing or support plan constraints.

Waiting for input…

AI Agent
Paperspace

What AI agents can do with Paperspace: 6 Tools for Infrastructure Management

Use these tools to get deep reads on your cloud infrastructure, from listing machine IDs to checking deployment logs.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Paperspace MCP

List Machines

Lists all bounded compute resources available within your Paperspace account limits.

Get Machine Details

Extracts detailed properties for a specific machine instance, including its current...

List Deployments

Retrieves explicit logs and statuses for cloud deployment targets.

List Notebooks

Inspects deep internal arrays to find details about specific AI workload notebooks.

List Projects

Enumerate structured project groupings, showing which team limits are currently...

Get User Details

Identifies precise account details and associated authentication arrays for the user.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Paperspace MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Paperspace integration is available immediately — no restart needed.

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 each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Paperspace, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Paperspace MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Paperspace. 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 CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The Manual Headache of Cloud Resource Auditing

Right now, figuring out the status of your compute environment means jumping between a dashboard, running separate CLI commands for deployments, and manually checking notebook IDs. You're copying resource IDs from one screen to another just to confirm if that GPU is actually free or if that container failed overnight. It's tedious, slow, and you always feel like you missed something.

With this MCP integrated into Vinkius, the entire process collapses into a single chat prompt. You ask your agent what's running—whether it’s an active machine core or a Jupyter notebook limit—and it delivers a clean, consolidated report instantly.

Paperspace MCP: Instant Infrastructure Visibility

You no longer have to manually check individual team projects or cross-reference machine IDs with project groupings. The agent uses `list_projects` and `get_machine_details` together, giving you a single view of the entire resource map.

The difference is control. Your AI client doesn't just read data; it structures complex cloud metadata into actionable intelligence in seconds.

What Paperspace MCP does for your AI

Managing distributed computing power is a headache until now. This MCP connects your AI agent directly to Paperspace Cloud Insights, giving you an immediate view of every active resource running in the cloud. You can query which physical machine cores are heavily modified or check memory schemas across different compute instances.

It’s also great for auditing who has access by checking native identity accounts and tracking team project limits. If your workflow requires knowing the status of deployed containers, this MCP handles that too. This level of deep infrastructure insight is what makes the Vinkius catalog so powerful; you get one connection point to dozens of specialized services.

You can use it to inspect raw Jupyter notebooks linked to specific deep learning models or even check if a serverless API container is available by reviewing its logs.

Built · Hosted · Managed by Vinkius Paperspace - GPU Workloads & Cloud Monitoring MCP
Server ID 019d75ee-db8c-73a3-b9bb-0ca4e354d0d4
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Paperspace MCP

How does Paperspace MCP help me find an idle GPU? +

You can use list_machines to see all available compute resources. Then, prompt your agent to run get_machine_details on those IDs to check their current load and memory usage.

Can I track which team owns a specific project using Paperspace MCP? +

Yes, running list_projects enumerates all structured groupings. This tool shows the active team limits attached to specific GPU units.

What if my container deployment log is corrupted? Can Paperspace MCP help? +

You can use list_deployments. The MCP reads explicit cloud logs, which helps verify whether the target deployment status remains active even if other logging methods fail.

Does Paperspace MCP only work for new ML projects? +

No. It monitors existing infrastructure too. Use list_notebooks to inspect old or dormant Jupyter notebooks and check their associated workload limits.

How do I know which user account is connected to this Paperspace MCP? +

Running the get_user_details tool identifies all active account arrays, confirming who has access credentials and what support plan they are under.