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Connect Paperspace to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Control your deep learning infrastructure through any AI client.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 6 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Paperspace.

  1. 01

    List machines

    This capability identifies all bounded compute resources within your Headless Paperspace limits.

  2. 02

    List deployments

    This capability retrieves cloud logging data to trace your explicit deployment targets.

  3. 03

    List notebooks

    This capability inspects internal arrays to help you manage specific AI workload limits in Jupyter.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Paperspace.

  1. 04

    List projects

    This capability enumerates your structured project rules and exports active team limits.

  2. 05

    Get user details

    Use this to identify the active identity arrays spanning your native authentication.

  3. 06

    Get machine details

    Use this to extract specific properties and structural logic driving your active instances.

Real work

What teams actually run

01

Resource Auditing

Check your current GPU footprint to ensure you aren't exceeding project limits.

02

Deployment Debugging

Use your agent to pull logs from serverless API containers when a deployment fails.

03

Notebook Management

Identify which Jupyter notebooks are consuming resources in your Gradient environment.

04

Team Oversight

Monitor how different team projects are utilizing allocated GPU units.

Automate a task

Put Paperspace to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Paperspace works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Paperspace to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

849ms average. Fast in production.

Paperspace is checked daily against the live service.

Daily averagePeak 957ms
Oct 3Today
Fastest day
653ms
Slowest day
957ms
14-day trend
Improving-12%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Paperspace, so you can see the experience inside your AI.

It does not authenticate your account with Paperspace. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Paperspace Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_w4nfco02fghsGPeqz307rO7rx1srVWdx33BhZToR/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Paperspace capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "paperspace-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_w4nfco02fghsGPeqz307rO7rx1srVWdx33BhZToR/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Paperspace in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Paperspace owners hand off.

This MCP is built for technical users managing heavy machine learning workloads in the cloud.

  • 01

    AI Developers

    They use the agent to map GPU allocations for heavy models directly from chat.

  • 02

    Infrastructure Ops

    They fetch deployment data to verify which container APIs are active.

  • 03

    ML Researchers

    They track lab setups by investigating Jupyter limits and RAM boundaries.

FAQ

Questions Paperspace owners ask.

  • 01

    How do I connect this MCP to my AI client?

    You subscribe via Vinkius and enter your Paperspace API Key. Once connected, you can use it immediately in any MCP-compatible client like Claude or Cursor.

  • 02

    What kind of hardware information can my agent see?

    Your agent can see specific machine details including GPU types, memory schemas, and storage constraints for your active instances.

  • 03

    Can I manage Jupyter notebooks with this?

    Yes, the MCP allows your agent to query raw Jupyter notebooks attached to Gradient models to check for idle constraints.

  • 04

    Is this compatible with my existing deployment workflows?

    Yes, it allows you to check container availability and pull logs for serverless API containers directly through your agent.

  • 05

    Does this work with team accounts?

    Yes, you can use it to trace collaborative groupings and check how GPU units map to specific team projects.

  • 06

    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.

  • 07

    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.

  • 08

    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.

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