Does this MCP only look at inference cost?

No. It goes beyond just the per-token cost. It includes the total cost of ownership, factoring in model switching costs and annual maintenance projections.

Can I use this to compare different LLM providers?

Yes. You provide the specs for multiple models, and the MCP compares their performance and cost profiles against your specific business requirements.

What if I don't know which model to use?

You can start by defining your non-negotiable constraints (e.g., 'must be under $0.01/1k tokens' and 'must be >90% accurate'). The MCP will narrow down the best options for you.

Is this useful for predicting future costs?

Absolutely. The predict_maintenance_impact capability specifically adjusts long-term cost projections based on how often the model requires updates or patches.

How does the engine handle accuracy requirements?

The recommend_optimal_model capability filters out any models that do not meet your specified minAccuracy threshold before selecting the most cost-effective option.

Can I calculate the cost of switching from one model to another?

Yes, use the analyze_model_switching capability. It factors in your one-time engineering costs and monthly volume to determine the payback period and net savings.

Does this account for model maintenance?

Yes, the predict_maintenance_impact capability allows you to include annual update frequency and labor costs to get a realistic total annual cost projection.

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Connect AI Model Selection Roi Engine 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. Stop guessing. Start building with data-backed model choices.

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 Model ROI Engine.

01
Recommend optimal model
Identifies the best model candidate based on a set of provided options and strict user constraints
02
Analyze model switching
Determines if migrating from a current model to a new candidate is economically beneficial
03
Calculate cost performance tradeoff
Quantifies the relationship between spending more money to gain higher accuracy or lower latency
04
Predict maintenance impact
Adjusts the long-term cost projections based on the frequency of model updates and maintenance needs

Real work

What teams actually run

Budget-Constrained MVP

You need to prove the concept with minimal spending. You use the MCP to recommend the cheapest model that still hits your minimum required accuracy.

Scaling an Existing Product

Your current model is hitting its cost ceiling. You run a tradeoff analysis to see if a slightly less accurate, but much cheaper, alternative is viable.

Model Refresh Cycle

It's time to upgrade your core LLM. You use the MCP to justify the $500 migration cost by showing the long-term savings.

Performance Optimization

You need to reduce latency below 300ms. You use the MCP to find the optimal model that achieves that speed without blowing the budget.

One connector, every AI

AI Model ROI 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.

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

You don't need a client to put AI Model ROI 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

847ms average. Fast in production.

AI Model ROI Engine is checked daily against the live service.

Daily averagePeak 1089ms

Oct 5Today

Fastest day: 723ms
Slowest day: 1089ms
14-day trend: Slowing+40%

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 Model ROI Engine, so you can see the experience inside your AI.

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

AI Model ROI Engine Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_P2JDx8XSXJThXWTdwTkMVQ0G0Agz0zxK0z3txYus/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 Model ROI Engine capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-model-selection-roi-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_P2JDx8XSXJThXWTdwTkMVQ0G0Agz0zxK0z3txYus/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 Model ROI Engine in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Model ROI Engine owners hand off.

This MCP is essential for anyone responsible for the financial and technical architecture of an AI product. If you're an AI Engineer, Product Manager, or ML Ops specialist, you'll use this to move model selection from guesswork to quantitative analysis.

01
AI Engineer
Uses it to test model viability against strict latency, cost, and accuracy requirements.
02
Product Manager
Uses it to build a business case, showing stakeholders the ROI of a specific model choice.
03
ML Ops Specialist
Uses it to plan model upgrades and calculate the true cost of switching infrastructure.

FAQ

Questions AI Model ROI Engine owners ask.

01
Does this MCP only look at inference cost?
No. It goes beyond just the per-token cost. It includes the total cost of ownership, factoring in model switching costs and annual maintenance projections.
02
Can I use this to compare different LLM providers?
Yes. You provide the specs for multiple models, and the MCP compares their performance and cost profiles against your specific business requirements.
03
What if I don't know which model to use?
You can start by defining your non-negotiable constraints (e.g., 'must be under $0.01/1k tokens' and 'must be >90% accurate'). The MCP will narrow down the best options for you.
04
Is this useful for predicting future costs?
Absolutely. The predict_maintenance_impact capability specifically adjusts long-term cost projections based on how often the model requires updates or patches.
05
How does the engine handle accuracy requirements?
The recommend_optimal_model capability filters out any models that do not meet your specified minAccuracy threshold before selecting the most cost-effective option.
06
Can I calculate the cost of switching from one model to another?
Yes, use the analyze_model_switching capability. It factors in your one-time engineering costs and monthly volume to determine the payback period and net savings.
07
Does this account for model maintenance?
Yes, the predict_maintenance_impact capability allows you to include annual update frequency and labor costs to get a realistic total annual cost projection.

Explore

More in Optimization

Connect AI Model ROI Engine 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

Recommend optimal model

Analyze model switching

Calculate cost performance tradeoff

Predict maintenance impact

What teams actually run

Budget-Constrained MVP

Scaling an Existing Product

Model Refresh Cycle

Performance Optimization

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

AI Model ROI Engine Connector

Claude Desktop

AI Engineer

Product Manager

ML Ops Specialist

Does this MCP only look at inference cost?

Can I use this to compare different LLM providers?

What if I don't know which model to use?

Is this useful for predicting future costs?

How does the engine handle accuracy requirements?

Can I calculate the cost of switching from one model to another?

Does this account for model maintenance?

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