Use Feedback Economics Engine with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Determine the financial value of your model improvements.
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.
Complete set · 4 capabilities
The complete Feedback Economics Engine capability set.
These are the exact actions your AI can choose when you ask it to work with Feedback Economics Engine.
01-04
4 capabilities in this set.
Part of 4 available through Feedback Economics Engine.
- 01
Analyze quality impact
Analyzes how changing feedback quality affects ROI
- 02
Calculate program economics
Calculates the total cost and the resulting ROI for current feedback parameters
- 03
Find optimal collection rate
Finds the optimal feedback collection rate to maximize economic return
- 04
Simulate volume scaling
Simulates how costs and ROI change as the user base grows
Observed, not estimated
833ms average. Fast in production.
Feedback Economics Engine is checked daily against the live service.
- Fastest day
- 753ms
- Slowest day
- 1105ms
- 14-day trend
- Improving-31%
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 Feedback Economics Engine, so you can see the experience inside your AI.
It does not authenticate your account with Feedback Economics Engine. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Feedback Economics Engine Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_XiDh9a8ToOhSkzADXMjBNH6Vzh89MJPIcVCK8grP/mcpClaude 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 — Feedback Economics Engine capabilities are ready to use.
{
"mcpServers": {
"ai-feedback-loop-economics-mcp": {
"url": "https://edge.vinkius.com/vk_preview_XiDh9a8ToOhSkzADXMjBNH6Vzh89MJPIcVCK8grP/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 Feedback Economics Engine owners hand off.
Product Managers, Data Scientists, and CTOs use this MCP to move beyond gut feelings about data collection. You get hard numbers on whether the effort to gather feedback is financially worthwhile. You can prove the value of your data initiatives to stakeholders.
- 01
Product Manager
Determines if the ROI from a new feature's feedback justifies the engineering effort.
- 02
Data Scientist
Calculates the optimal balance between feedback volume and data quality for model training.
- 03
CTO / VP of Product
Models the financial impact of scaling the user base and improving core AI capabilities.
FAQ
Questions Feedback Economics Engine owners ask.
- 01
Does this MCP help with scaling my product?
Yes. You can use the simulate volume scaling capability to project how both costs and ROI change as your user base grows. This helps you plan for future growth scenarios.
- 02
What inputs do I need to run the calculations?
You need core metrics like user count, processing cost per feedback, the current feedback rate, and the estimated value of model improvement.
- 03
Can I find out the best rate for collecting feedback?
The find optimal collection rate capability determines the ideal percentage of users to collect feedback from. This helps you maximize your economic return.
- 04
Is this just for large companies?
No. You can use it to model the financial impact of feedback collection, regardless of your current size, to make data collection a strategic decision.
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