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Connect Code Review Economics 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. Turn engineering review metrics into hard dollar values.

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.

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 Code Review Economics.

  1. 01

    Evaluate tool effectiveness

    This capability calculates if the money you spend on code review software actually pays off. It compares capability costs against the value of defects caught to justify your budget.

  2. 02

    Estimate team economics

    This capability models how review effort is distributed across your engineers. It helps you understand how team size changes your review density and cost per developer.

  3. 03

    Analyze review depth

    This capability checks if your team is spending the right amount of time on PRs. It identifies if your current process is under-reviewed, over-reviewed, or perfectly balanced.

  4. 04

    Calculate review roi

    This capability computes the total financial return on your review process. It weighs the cost of engineering time against the value of the bugs you prevent from reaching production.

Real work

What teams actually run

01

Budget Planning

Use the AI to decide if a new automated testing capability will pay for itself this year.

02

Process Optimization

Check if your team's review depth is optimal to prevent burnout or missed bugs.

03

Team Scaling

Model how adding five new developers will change your review cost distribution.

04

Performance Reporting

Generate ROI figures to show leadership the value of the engineering department.

One connector, every AI

Code Review 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.

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 Code Review 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

914ms average. Fast in production.

Code Review Economics is checked daily against the live service.

Daily averagePeak 1107ms
Oct 3Today
Fastest day
678ms
Slowest day
1107ms
14-day trend
Slowing+19%

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

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

Code Review Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Nae35izYLXuYYDe7RnJPqNL9B6MN7qJhwcZlUNe0/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 — Code Review Economics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "code-review-economics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Nae35izYLXuYYDe7RnJPqNL9B6MN7qJhwcZlUNe0/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 Code Review Economics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Code Review Economics owners hand off.

Engineering leaders who need to prove the value of their processes to stakeholders.

  • 01

    Engineering Managers

    They hand off review metrics to the AI to justify headcount or capability spend.

  • 02

    CTOs

    They use the AI to get a high-level view of engineering efficiency and ROI.

  • 03

    DevOps Leads

    They use the AI to measure the economic impact of CI/CD and review tooling.

FAQ

Questions Code Review Economics owners ask.

  • 01

    How does this MCP calculate ROI?

    It compares the cost of engineering hours and capability subscriptions against the financial value of the defects caught during the review process.

  • 02

    Can I use this with Cursor or VS Code?

    Yes, you can connect this MCP to any compatible client including Cursor, Windsurf, and VS Code.

  • 03

    What is review depth?

    Review depth is a measure of whether your team is spending too much or too little time on code reviews relative to the number of defects found.

  • 04

    Do I need to host this myself?

    No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

  • 05

    Can this help me justify buying new software?

    Yes, the evaluate_tool_effectiveness capability is specifically designed to show the economic justification for capability investments.

  • 06

    How do I calculate the ROI of my reviews?

    You can use the calculate_review_roi capability by providing the total review hours, the rework cost avoided, the cost of capabilities used, and the team size.

  • 07

    Can this capability help justify buying new linting or static analysis capabilities?

    Yes, the evaluate_tool_effectiveness capability specifically calculates if the investment in review capabilities is justified by the value of defects they help avoid.

  • 08

    How does team size affect the results?

    The estimate_team_economics capability analyzes how team size impacts the cost per engineer and the overall review density across your organization.

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