What kind of data does this MCP need to run?

The MCP requires metrics related to model performance decay, the current age of the model, and the rate of improvement in the state-of-the-art (SOTA) within your domain.

Is this for all types of AI models?

It's designed for any model whose utility degrades over time. You can use it for NLP, image recognition, financial forecasting, and more.

Does this tell me how much money to spend?

It doesn't give a dollar amount, but it tells you the urgency and the timing for reinvestment, allowing you to accurately budget for the required research and compute cycles.

What is the difference between depreciation rate and obsolescence velocity?

They measure the same thing: how fast the model's value is dropping. The MCP calculates the effective depreciation rate, which is the total velocity of that obsolescence.

How do I calculate the total obsolescence velocity?

You can use the get_effective_depreciation_rate capability, which combines the model's internal performance decay with the external SOTA improvement rate.

Can this capability help with R&D budget planning?

Yes, by using assess_rd_intensity, you can estimate the necessary research investment required to maintain a specific performance gap against the current SOTA.

How do I know if my retraining frequency is enough?

Use the analyze_retraining_adequacy capability to evaluate if your current retraining schedule keeps utility loss within safe margins.

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Connect AI Model Depreciation Rate 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. Know exactly when and how much to reinvest.

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 Depreciation Rate.

01
Analyze retraining adequacy
This checks if your current retraining schedule is actually sufficient to keep the model's utility high enough for production use.
02
Assess rd intensity
It estimates the necessary research investment required to counteract the natural decay of your model and keep it competitive.
03
Calculate reinvestment timing
Use this to determine the precise window when your next model upgrade or retraining cycle must happen to maintain performance.
04
Get effective depreciation rate
This capability calculates the total velocity of model obsolescence, giving you a single number for how fast your model is losing value.

Real work

What teams actually run

Financial Forecasting Models

Determine if a credit risk model needs retraining because industry standards (SOTA) have advanced significantly since its last update.

Natural Language Processing (NLP)

Calculate the depreciation rate for a chatbot model that is falling behind the latest conversational understanding benchmarks.

Image Recognition Systems

Assess if a visual inspection model is still adequate given the increasing complexity of real-world inputs and new detection standards.

Predictive Maintenance

Verify if the model used to predict equipment failure is still accurate enough to justify its continued use in the field.

One connector, every AI

AI Model Depreciation Rate 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 Depreciation Rate 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

911ms average. Fast in production.

AI Model Depreciation Rate is checked daily against the live service.

Daily averagePeak 1158ms

Oct 3Today

Fastest day: 742ms
Slowest day: 1158ms
14-day trend: Improving-11%

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 Depreciation Rate, so you can see the experience inside your AI.

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

AI Model Depreciation Rate Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_kYQVFMJPx1ZCpbONse8wxW11VdH8QJvgcxqH0JWA/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 Depreciation Rate capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-model-depreciation-rate-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_kYQVFMJPx1ZCpbONse8wxW11VdH8QJvgcxqH0JWA/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 Depreciation Rate in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Model Depreciation Rate owners hand off.

If you manage ML pipelines or own mission-critical AI systems, you need this. This MCP gives you the metrics to prove when a model is failing, allowing you to budget and plan upgrades before performance drops. It's for the people who can't afford unexpected downtime.

01
ML Engineer
Use it to validate if current retraining schedules are sufficient or if the model needs immediate intervention.
02
Data Scientist
Run analyses to determine the effective depreciation rate and estimate necessary research investment.
03
CTO / VP of Engineering
Use it to plan long-term model lifecycles and allocate compute resources based on predicted obsolescence.

FAQ

Questions AI Model Depreciation Rate owners ask.

01
What kind of data does this MCP need to run?
The MCP requires metrics related to model performance decay, the current age of the model, and the rate of improvement in the state-of-the-art (SOTA) within your domain.
02
Is this for all types of AI models?
It's designed for any model whose utility degrades over time. You can use it for NLP, image recognition, financial forecasting, and more.
03
Does this tell me how much money to spend?
It doesn't give a dollar amount, but it tells you the urgency and the timing for reinvestment, allowing you to accurately budget for the required research and compute cycles.
04
What is the difference between depreciation rate and obsolescence velocity?
They measure the same thing: how fast the model's value is dropping. The MCP calculates the effective depreciation rate, which is the total velocity of that obsolescence.
05
How do I calculate the total obsolescence velocity?
You can use the get_effective_depreciation_rate capability, which combines the model's internal performance decay with the external SOTA improvement rate.
06
Can this capability help with R&D budget planning?
Yes, by using assess_rd_intensity, you can estimate the necessary research investment required to maintain a specific performance gap against the current SOTA.
07
How do I know if my retraining frequency is enough?
Use the analyze_retraining_adequacy capability to evaluate if your current retraining schedule keeps utility loss within safe margins.

Explore

More in Analytics

Connect AI Model Depreciation Rate 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

Analyze retraining adequacy

Assess rd intensity

Calculate reinvestment timing

Get effective depreciation rate

What teams actually run

Financial Forecasting Models

Natural Language Processing (NLP)

Image Recognition Systems

Predictive Maintenance

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

AI Model Depreciation Rate Connector

Claude Desktop

ML Engineer

Data Scientist

CTO / VP of Engineering

What kind of data does this MCP need to run?

Is this for all types of AI models?

Does this tell me how much money to spend?

What is the difference between depreciation rate and obsolescence velocity?

How do I calculate the total obsolescence velocity?

Can this capability help with R&D budget planning?

How do I know if my retraining frequency is enough?

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