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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Improvement Velocity Tracker with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Know exactly how fast your product is evolving.

Included with plan

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

Complete set · 4 capabilities

The complete AI Improvement Velocity Tracker capability set.

These are the exact actions your AI can choose when you ask it to work with AI Improvement Velocity Tracker.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Improvement Velocity Tracker.

  1. 01

    Calculate feedback efficiency

    This capability analyzes how well your team converts raw user feedback into actual model upgrades, giving you an efficiency index.

  2. 02

    Get satisfaction metrics

    Use this to correlate specific model improvements with changes in overall user sentiment.

  3. 03

    Get velocity summary

    Get a high-level, immediate overview of your current AI product improvement performance and velocity score.

  4. 04

    Analyze improvement latency

    Measure the exact time delay in your improvement loop, from feedback collection to model deployment.

Observed, not estimated

830ms average. Fast in production.

AI Improvement Velocity Tracker is checked daily against the live service.

Daily averagePeak 984ms
Aug 28Today
Fastest day
741ms
Slowest day
984ms
14-day trend
Slowing+7%

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 Improvement Velocity Tracker, so you can see the experience inside your AI.

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

AI Improvement Velocity Tracker Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dQzng4QoJaqbS57UQHtGMuMs1WvepoF2N1hAtXhx/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 — AI Improvement Velocity Tracker capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-improvement-velocity-tracker-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dQzng4QoJaqbS57UQHtGMuMs1WvepoF2N1hAtXhx/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

Who it's for

Built for the work AI Improvement Velocity Tracker owners hand off.

This MCP is essential for product teams that rely on continuous AI iteration. If your job involves managing the lifecycle of a machine learning product, this capability gives you the quantitative data you need to prove product value and justify resource allocation.

  • 01

    Product Manager

    Use this to report on the speed and efficiency of the product's iterative development cycle.

  • 02

    ML Engineer

    Use this to benchmark the performance of the feedback loop and identify bottlenecks in the deployment process.

  • 03

    Product Owner

    Use this to correlate specific model updates with measurable changes in user satisfaction and adoption.

FAQ

Questions AI Improvement Velocity Tracker owners ask.

  • 01

    What does 'AI improvement velocity' actually measure?

    It measures the speed and effectiveness of your product's ability to incorporate user feedback and deploy model upgrades. It gives you a single score that summarizes the health of your entire feedback loop.

  • 02

    Do I need to manually feed the data into the MCP?

    No. The MCP connects to your existing data sources to calculate metrics like feedback efficiency and latency. You just need to ask your agent for the specific analysis you want.

  • 03

    Can this help me prove ROI on my ML team?

    Yes. By correlating model changes with user sentiment and calculating the implementation rate, you get hard numbers that prove your development efforts are moving the product forward.

  • 04

    What is the difference between efficiency and latency?

    Efficiency measures how well you turn feedback into upgrades. Latency measures how long it takes to get that upgrade out the door. Both are critical to product speed.

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