Does this MCP calculate emotional damage?

It quantifies intangible damage to user trust and retention, which is a proxy for emotional or reputational damage. It provides a measurable impact score rather than an emotional reading.

What kind of data do I need to run this?

You need data points like your error rate percentage, the cost associated with retrying a request, and the cost of falling back to a secondary system.

Can I use this to compare different system designs?

Yes, the MCP includes a capability that compares the total cost of 'Retry-heavy' versus 'Fallback-heavy' architectures, helping you pick the most efficient design.

Is this only for financial losses?

No. While it calculates direct financial loss, it also assesses the non-monetary impact on user experience and trust.

What is ROI in this context?

ROI stands for Return on Investment. The MCP uses it to determine if the money you spend on preventing errors (like fine-tuning) saves you more money than it costs.

How does this capability calculate the direct cost of errors?

The get_error_cost_summary capability calculates the sum of all retry attempts and fallback executions triggered by the specified error rate and request volume.

Can I model the impact of graceful degradation?

Yes, analyze_user_experience_impact includes a parameter to account for graceful degradation, which reduces the final user impact score by providing partial utility.

How do I know if a fix is worth the investment?

You can use calculate_prevention_roi to compare the cost of implementing an improvement against the expected savings from a reduced error rate.

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Connect AI Error Recovery Economics 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. Model recovery strategies and calculate ROI for system reliability.

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 Error Recovery Economics.

01
Analyze user experience impact
Quantifies the intangible damage to user trust and retention caused by errors
02
Calculate prevention roi
Determines if investing in error reduction is financially sound
03
Compare recovery strategies
Compares the cost of "Retry-heavy" vs "Fallback-heavy" architectures
04
Get error cost summary
Calculates the total direct financial loss caused by AI errors

Real work

What teams actually run

Pre-Launch Reliability Audit

Before launching a new feature, you run the MCP to model the potential cost of failure, giving you a concrete budget for error handling.

Justifying Technical Debt

Your team needs more time to fix bugs. Use the ROI calculation to prove that the cost of delay outweighs the cost of the fix.

System Architecture Review

You must choose between a complex retry system or a simple fallback. The MCP compares the total cost of both approaches.

Stakeholder Reporting

You need to explain AI failure costs to executives. You use the MCP to provide a single, quantified summary of financial and experiential damage.

One connector, every AI

AI Error Recovery 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 Error Recovery 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

851ms average. Fast in production.

AI Error Recovery Economics is checked daily against the live service.

Daily averagePeak 1165ms

Oct 3Today

Fastest day: 688ms
Slowest day: 1165ms
14-day trend: Slowing+37%

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

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

AI Error Recovery Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_kgwOd6Q0SAbimPFnFjAsm6LUneLAejFRzONNQsRN/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 Error Recovery Economics capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-error-recovery-economics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_kgwOd6Q0SAbimPFnFjAsm6LUneLAejFRzONNQsRN/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 Error Recovery Economics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI Error Recovery Economics owners hand off.

If you're responsible for the reliability or financial health of an AI product, this MCP is for you. It moves the conversation beyond 'it failed' to 'how much did it cost us.'

01
Product Manager
Use it to justify feature improvements by quantifying the current cost of failure.
02
CTO / Engineering Lead
Use it to compare the cost-effectiveness of different system architectures.
03
Risk Analyst
Use it to model the financial impact of potential AI inaccuracies before deployment.

FAQ

Questions AI Error Recovery Economics owners ask.

01
Does this MCP calculate emotional damage?
It quantifies intangible damage to user trust and retention, which is a proxy for emotional or reputational damage. It provides a measurable impact score rather than an emotional reading.
02
What kind of data do I need to run this?
You need data points like your error rate percentage, the cost associated with retrying a request, and the cost of falling back to a secondary system.
03
Can I use this to compare different system designs?
Yes, the MCP includes a capability that compares the total cost of 'Retry-heavy' versus 'Fallback-heavy' architectures, helping you pick the most efficient design.
04
Is this only for financial losses?
No. While it calculates direct financial loss, it also assesses the non-monetary impact on user experience and trust.
05
What is ROI in this context?
ROI stands for Return on Investment. The MCP uses it to determine if the money you spend on preventing errors (like fine-tuning) saves you more money than it costs.
06
How does this capability calculate the direct cost of errors?
The get_error_cost_summary capability calculates the sum of all retry attempts and fallback executions triggered by the specified error rate and request volume.
07
Can I model the impact of graceful degradation?
Yes, analyze_user_experience_impact includes a parameter to account for graceful degradation, which reduces the final user impact score by providing partial utility.
08
How do I know if a fix is worth the investment?
You can use calculate_prevention_roi to compare the cost of implementing an improvement against the expected savings from a reduced error rate.

Explore

More in Finance

Connect AI Error Recovery 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

Analyze user experience impact

Calculate prevention roi

Compare recovery strategies

Get error cost summary

What teams actually run

Pre-Launch Reliability Audit

Justifying Technical Debt

System Architecture Review

Stakeholder Reporting

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

AI Error Recovery Economics Connector

Claude Desktop

Product Manager

CTO / Engineering Lead

Risk Analyst

Does this MCP calculate emotional damage?

What kind of data do I need to run this?

Can I use this to compare different system designs?

Is this only for financial losses?

What is ROI in this context?

How does this capability calculate the direct cost of errors?

Can I model the impact of graceful degradation?

How do I know if a fix is worth the investment?

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