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Vinkius

Paperspace Connector for AI agents.

6 live capabilities

Manage your GPU workloads and deep learning instances without leaving your editor.

Live agent request Paperspace / Connector

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AI Agent

Why people use Paperspace

Paperspace for GPU Infrastructure Management

With this Connector, you just ask your AI client. It pulls the data for you and summarizes it in one place. You get the answer you need without the tab-switching.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a live dashboard of your machine learning infrastructure inside your AI chat.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Checking GPU availability for a new run

    An ML researcher is unsure which machine has free memory.

  2. Real-world use case 02

    Verifying a production deployment

    An infra lead needs to know if the new API container is live.

  3. Real-world use case 03

    Audit team project limits

    A manager needs to see if the team is staying within the storage ceiling.

Complete set · 6capabilities

The complete Paperspace capability set.

These are the exact actions your AI can choose when you ask it to work with Paperspace.

Capability set01 / 02

01—03

3 capabilities in this set.

Part of 6 available through Paperspace.

  1. 01 Capability

    List deployments

    Pull explicit Cloud logging and trace your deployment targets. Use this to see if your containers are active.

  2. 02 Capability

    List notebooks

    Inspect internal arrays to see which AI workloads are using notebooks. This is great for tracking deep learning tasks.

  3. 03 Capability

    List projects

    See the structured rules and team limits for your active projects. It helps you manage your team's budget.

Capability set02 / 02

04—06

3 capabilities in this set.

Part of 6 available through Paperspace.

  1. 04 Capability

    List machines

    View all your bounded Compute resources in the Headless Paperspace limits. This helps you see what is running at a glance.

  2. 05 Capability

    Get machine details

    Get the specific properties and logic driving an active instance. You can check memory and storage constraints quickly.

  3. 06 Capability

    Get user details

    Identify the active arrays spanning your native Identity Auth. Use this to check account permissions.

Set up in minutes

One URL. Then ask Paperspace to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Paperspace from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_w4nfco02fghsGPeqz307rO7rx1srVWdx33BhZToR/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Paperspace, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Paperspace for the conversation.

Where the request belongs

Work Paperspace can move forward.

Built around the request

This is for the ML engineer who needs to monitor GPU health without leaving their IDE, the infrastructure lead tracking cloud spend, and the data scientist managing a fleet of Jupyter notebooks.

01

ML Researcher

Tracks Jupyter limits and RAM boundaries for training runs on a Tuesday afternoon.

02

Infrastructure Ops

Verifies container APIs and active deployments to ensure production stability.

03

AI Developer

Maps GPU allocations for heavy model testing to stay within team budget limits.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
Lambda Labs (GPU Cloud) logo
01 7 capabilities

Lambda Labs (GPU Cloud)

Manage AI infrastructure via Lambda Labs. launch GPU instances, monitor ML workloads, and manage SSH keys.

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RunPod logo
02 7 capabilities

RunPod

Integrate your AI securely to RunPod to cleanly quickly provision scalable GPU pods, manage active instances, and inspect serverless endpoints and custom templates natively.

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Vast.ai (GPU Rental Cloud API) logo
03 4 capabilities

Vast.ai (GPU Rental Cloud API)

Rent high-performance GPUs for AI and deep learning. Search marketplace offers, deploy Docker containers, and manage your cloud GPU fleet.

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Modal (Serverless AI Infrastructure) logo
04 7 capabilities

Modal (Serverless AI Infrastructure)

Manage serverless compute via Modal. audit active apps, track GPU deployments, and monitor network volumes.

View Connector
Gridscale (IaaS & PaaS Cloud Hosting API) logo
05 17 capabilities

Gridscale (IaaS & PaaS Cloud Hosting API)

Manage your Gridscale cloud infrastructure. provision servers, monitor metrics, and control PaaS services directly from any AI agent.

View Connector
Flystack logo
06 5 capabilities

Flystack

Manage cloud infrastructure. audit deployments, clusters, and metrics via AI.

View Connector

Bring your own AI

Change the model, client or framework. Keep Paperspace connected.

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Before you connect

Questions about Paperspace.

The practical details behind the request, access and result.

Can I see my GPU usage with Paperspace MCP?

Yes. You can ask your agent to list all active machines and see which ones are running, their status, and their hardware specs.

How do I check my Jupyter notebooks using Paperspace MCP?

You can ask your agent to list your notebooks. It will show you which ones are active and which ones are tied to your current deep learning tasks.

Can Paperspace MCP help me manage my team's project limits?

Yes. It can pull the structured rules and team limits for your active projects so you can stay within your budget.

Does Paperspace MCP show my deployment logs?

It can pull explicit cloud logging for your deployments to help you see if your containers are active and running correctly.

How do I find active machines on Paperspace MCP?

Just ask your agent to list your machines. It will provide a summary of your bounded compute resources in your chat window.

Can I use Paperspace MCP with Cursor or Claude?

Yes. This Connector is designed to work with any MCP-compatible client, including Claude, Cursor, and Windsurf.

Are Paperspace Core machines dynamically mapped?

Yes. The list_machines query returns deeply structured attributes associated exactly with the base compute objects provisioning storage arrays, IPs, and states running natively over Paperspace Core.

Can I spin up new Jupyter Gradient instances?

Currently, this module focuses strictly on dynamic observability. pulling down Notebooks arrays, Teams constraints, and extracting native deploy mapping contexts. Write operations to spin up environments are out-of-scope for read workflows.

How do I fetch the resource specs belonging to a specific ID?

After listing the overall arrays, provide the psxxxxxx ID identifier securely to the get_machine_details extractor to generate raw hardware limitations mapped logically inside that node.

One connection away

Give your agent a direct line to Paperspace.

Connect Paperspace once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available