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Connect AI Hardware Iteration Risk to ChatGPT and Claude

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. Plan compute refreshes before performance gaps hit.

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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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Hardware Risk Engine.

  1. 01

    Determine timing strategy tool

    Determines the optimal moment to execute a hardware refresh

  2. 02

    Estimate refresh investment tool

    Estimates the capital expenditure required to replace existing capacity with next-gen hardware

  3. 03

    Calculate obsolescence risk tool

    Calculates the risk that current hardware becomes obsolete before its scheduled replacement

  4. 04

    Get hardware evolution forecast tool

    Provides historical and projected rates of change for specific GPU generations

Real work

What teams actually run

01

Annual Budget Planning

A finance team uses the MCP to estimate the total capital expenditure required to replace 50 units of current hardware with next-gen units.

02

Mid-Cycle Risk Assessment

An infrastructure architect runs the obsolescence risk check to see if current GPU generations are at high risk of failure before the next planned refresh.

03

Strategic Upgrade Timing

A technical lead uses the MCP to determine if they should upgrade immediately or wait, based on current utilization and predicted performance uplift.

04

Technology Roadmap Planning

A team uses the hardware evolution forecast to build a 5-year roadmap, tracking performance changes across different GPU generations.

One connector, every AI

AI Hardware Risk Engine 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 AI Hardware Risk Engine 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

870ms average. Fast in production.

AI Hardware Risk Engine is checked daily against the live service.

Daily averagePeak 1157ms
Oct 3Today
Fastest day
754ms
Slowest day
1157ms
14-day trend
Slowing+36%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 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 AI Hardware Risk Engine, so you can see the experience inside your AI.

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

AI Hardware Risk Engine Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_ubWUj3SNzbyobadlL7rKDPH8dDjsYle4s8lszKc8/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 — AI Hardware Risk Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-hardware-iteration-risk-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ubWUj3SNzbyobadlL7rKDPH8dDjsYle4s8lszKc8/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 AI Hardware Risk Engine in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Hardware Risk Engine owners hand off.

This MCP is essential for infrastructure architects, CTOs, and finance teams managing large-scale AI compute resources. If your organization relies on high-performance computing and needs to plan for hardware refreshes, this capability gives you the data to make capital expenditure decisions.

  • 01

    Infrastructure Architect

    Determines the technical debt and calculates the risk of using aging GPU generations.

  • 02

    CTO / VP of Engineering

    Uses the MCP to set long-term compute strategy and plan for necessary hardware upgrades.

  • 03

    Financial Planner

    Estimates the capital expenditure required for hardware refreshes and budgets for future compute needs.

FAQ

Questions AI Hardware Risk Engine owners ask.

  • 01

    Does this MCP help with general hardware maintenance?

    No. This MCP focuses specifically on the lifecycle and obsolescence risk of high-performance AI compute infrastructure, particularly GPU generations. It helps you plan major refreshes, not routine maintenance.

  • 02

    What kind of data does it use for forecasting?

    It uses historical and projected performance uplift data for specific GPU generations. This allows you to benchmark your current setup against expected industry improvements.

  • 03

    Is this capability only for large data centers?

    While designed for large-scale compute, it helps any organization that needs to manage the technical debt and capital expenditure associated with rapidly evolving AI hardware.

  • 04

    Can I get a cost estimate for my upgrade?

    Yes. You can use the estimate_refresh_investment_tool to calculate the total capital expenditure needed to replace your existing capacity with next-generation hardware.

  • 05

    How do I calculate the risk of my current GPUs becoming obsolete?

    You can use the calculate_obsolescence_risk capability. Provide the current GPU generation, the months remaining until the next-gen release, the expected performance uplift, and your standard refresh cycle. Capabilities available: calculate_obsolescence_risk_tool, estimate_refresh_investment_tool, determine_timing_strategy_tool.

  • 06

    Can this capability help with budgeting for new hardware?

    Yes, the estimate_refresh_investment capability calculates the total investment required for a refresh, accounting for performance improvements that might allow for fewer units.

  • 07

    How does the capability determine the best time to upgrade?

    The determine_timing_strategy capability weighs the risk of obsolescence against the cost of capital and current hardware utilization to recommend an action.

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