Does this MCP account for power costs?

Yes. The models require inputs like power cost per kWh and the GPU's power draw, ensuring the calculations are based on real-world operational expenses.

Can I use this for multiple GPU types?

The capabilities are designed to handle fleet-level metrics, allowing you to estimate total revenue and profit across multiple units.

Is this just a calculator, or does it do more?

It's more than a calculator. It uses economic models to analyze risk, such as assessing how rapid hardware advancement affects your overall ROI.

What kind of data do I need to provide?

You need core metrics like initial investment cost, hourly revenue rate, utilization percentage, and operational costs (like power draw and cost per kWh).

How do I calculate the payback period for my GPU fleet?

You can use the calculate_payback_period capability. Provide the total number of GPUs, their cost, hourly revenue, utilization rate, power costs, and average power draw.

What is the minimum utilization needed to be profitable?

Use the find_breakeven_utilization capability. It calculates the specific percentage of time a GPU must be active to cover both depreciation and electricity costs.

Does this model account for hardware becoming obsolete?

Yes, the analyze_obsolescence_risk capability allows you to factor in a decay multiplier to see how rapid technological advancement affects your ROI.

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Connect AI Infrastructure GPU Economics to your AI

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. Know the true ROI of your GPU investments.

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.

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.

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 Infrastructure Economics.

01
Calculate payback period
Calculates the number of months required to recover initial investment
02
Analyze obsolescence risk
Analyzes how rapid hardware advancement affects ROI
03
Find breakeven utilization
Calculates the minimum utilization required to avoid losing money
04
Get gpu revenue metrics
Calculates total revenue and profit-per-unit for a GPU fleet

Real work

What teams actually run

Planning a Fleet Expansion

Before buying 50 new GPUs, run the metrics to confirm the projected revenue justifies the capital outlay.

Optimizing Utilization

If current utilization is low, use the break-even capability to see how much capacity you need just to break even.

Budgeting for Refresh Cycles

Assess obsolescence risk to build a realistic, financially sound hardware refresh budget for the next three years.

Comparing Compute Options

Run the revenue metrics on different GPU models to see which offers the best profit per unit.

One connector, every AI

AI Infrastructure Economics 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.

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

You don't need a client to put AI Infrastructure Economics 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

919ms average. Fast in production.

AI Infrastructure Economics is checked daily against the live service.

Daily averagePeak 1053ms

Oct 3Today

Fastest day: 645ms
Slowest day: 1053ms
14-day trend: Slowing+5%

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 Infrastructure Economics, so you can see the experience inside your AI.

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

AI Infrastructure Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_bs8nrsx1alJqvHF4VtG9oDyP7k8v2vVLHshBsx9e/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — AI Infrastructure Economics capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-infrastructure-gpu-economics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bs8nrsx1alJqvHF4VtG9oDyP7k8v2vVLHshBsx9e/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 Infrastructure Economics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Infrastructure Economics owners hand off.

This MCP is built for technical leaders and financial analysts who manage large-scale compute infrastructure. If you're responsible for capital expenditure decisions or optimizing data center efficiency, this capability gives you the hard numbers you need to justify hardware purchases.

01
CTO / VP of Infrastructure
Use this to build business cases for new hardware purchases and justify expansion budgets.
02
Financial Analyst
Run these models to accurately forecast revenue streams and calculate true cost recovery timelines.
03
Data Center Manager
Check utilization metrics to ensure the facility is operating above the break-even threshold.

FAQ

Questions AI Infrastructure Economics owners ask.

01
Does this MCP account for power costs?
Yes. The models require inputs like power cost per kWh and the GPU's power draw, ensuring the calculations are based on real-world operational expenses.
02
Can I use this for multiple GPU types?
The capabilities are designed to handle fleet-level metrics, allowing you to estimate total revenue and profit across multiple units.
03
Is this just a calculator, or does it do more?
It's more than a calculator. It uses economic models to analyze risk, such as assessing how rapid hardware advancement affects your overall ROI.
04
What kind of data do I need to provide?
You need core metrics like initial investment cost, hourly revenue rate, utilization percentage, and operational costs (like power draw and cost per kWh).
05
How do I calculate the payback period for my GPU fleet?
You can use the calculate_payback_period capability. Provide the total number of GPUs, their cost, hourly revenue, utilization rate, power costs, and average power draw.
06
What is the minimum utilization needed to be profitable?
Use the find_breakeven_utilization capability. It calculates the specific percentage of time a GPU must be active to cover both depreciation and electricity costs.
07
Does this model account for hardware becoming obsolete?
Yes, the analyze_obsolescence_risk capability allows you to factor in a decay multiplier to see how rapid technological advancement affects your ROI.

Explore

More in Infrastructure

Connect AI Infrastructure Economics to Claude, Cursor, ChatGPT & more

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

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Calculate payback period

Analyze obsolescence risk

Find breakeven utilization

Get gpu revenue metrics

What teams actually run

Planning a Fleet Expansion

Optimizing Utilization

Budgeting for Refresh Cycles

Comparing Compute Options

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

AI Infrastructure Economics Connector

Claude Desktop

CTO / VP of Infrastructure

Financial Analyst

Data Center Manager

Does this MCP account for power costs?

Can I use this for multiple GPU types?

Is this just a calculator, or does it do more?

What kind of data do I need to provide?

How do I calculate the payback period for my GPU fleet?

What is the minimum utilization needed to be profitable?

Does this model account for hardware becoming obsolete?

AI App Rate Limiting Economics AI Connector

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