Enterprise AI & Workplace Automation CoconutSubmitted July 18, 2026

Verdict : Every proposal deserves a verdict, not just an approval.

An MCP app on the Model Context Protocol built by Coconut at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

Verdict is an agentic MCP application that stress-tests business proposals before they reach a real board. Submit any plan and five adversarial AI personas — a Skeptical Investor, Regulator, Competitor, Disgruntled Customer, and Future Historian — independently analyze it using real MCP tools, argue with each other in a live transcript, and deliver a verdict that preserves unresolved disagreement instead of a single smoothed-over answer.

Enterprise AI & Workplace Automation track

Develop AI agents and automation tools that improve productivity, streamline workflows, and enhance business operations.

Live MCP appSource code

Team Coconut

  • Abhinav DileepLead

  • Parthiv M

  • Hari Sankar A

  • AYYAPPADAS MT

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Frequently asked questions

What does Verdict : Every proposal deserves a verdict, not just an approval. do?
Verdict is an agentic MCP application that stress-tests business proposals before they reach a real board. Submit any plan and five adversarial AI personas — a Skeptical Investor, Regulator, Competitor, Disgruntled Customer, and Future Historian — independently analyze it using real MCP tools, argue with each other in a live transcript, and deliver a verdict that preserves unresolved disagreement instead of a single smoothed-over answer.
Who built Verdict : Every proposal deserves a verdict, not just an approval.?
Verdict : Every proposal deserves a verdict, not just an approval. was built by team Coconut at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon, in the Enterprise AI & Workplace Automation track.
What is an MCP app and how is it built?
An MCP app is an application built on the Model Context Protocol — an open standard that lets AI agents connect to tools, data, and APIs. This project exposes MCP tools and resources that agentic AI systems can call. It was built and deployed on NitroStack, the full-stack platform for shipping MCP apps and servers.