BFSI & FinTech Gojo Protocol🔥Submitted July 18, 2026

CredEdge — an MCP server that turns AI into a real bank employee for fraud, credit & lending

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

About this project

CredEdge is an MCP server built for the BFSI & FinTech track that gives an AI agent real, live access to the core functions a bank employee performs every day — not a chatbot that talks about finance, but one that actually acts on real account data. It exposes six tools: real-time fraud risk scoring (analyzes a transaction against the account's actual spend history — amount, location, velocity, merchant pattern — and returns a fraud probability with a concrete next-action plan), CIBIL score lookup, personal loan eligibility (explains exactly why a loan is approved or rejected and lists the documents needed — aligned with RBI's Digital Lending Guidelines on rejection transparency), SME business loan assessment (turnover, GST compliance, years in operation), insurance claim investigation (flags early claims, high-value claims, and repeat-claimant patterns), and personalized financial advice (turns income/debt data into a concrete monthly savings and investment plan). It also pulls live market data via Alpha Vantage as a real external data signal. Every tool result renders as a polished visual widget inside the AI chat itself — risk gauges, eligibility cards, CIBIL score dials — with one-click PDF/Word export for compliance record-keeping. Who it's for: banks, NBFCs, and fintechs that want to give an AI assistant safe, auditable access to lending and fraud decisions without exposing raw databases — the AI only ever sees what a tool explicitly returns. What makes it special: because it's built on MCP rather than a one-off API, the exact same server works unmodified inside Claude, ChatGPT, or any future MCP-compatible banking assistant — one build, many front doors. Every decision is explainable, since a resource exposes the underlying rulebook, so an examiner can ask why a decision was made and get the exact rule that fired — not a black box.

BFSI & FinTech track

Build AI solutions for banking, payments, insurance, fraud detection, lending, and financial inclusion.

Team Gojo Protocol🔥

  • BONDADA MANOJ KUMARLead

  • Yashwanth kommineni

  • MUMMADI MANJUNADHA REDDY

  • Niketh S Nair

Frequently asked questions

What does CredEdge — an MCP server that turns AI into a real bank employee for fraud, credit & lending do?
CredEdge is an MCP server built for the BFSI & FinTech track that gives an AI agent real, live access to the core functions a bank employee performs every day — not a chatbot that talks about finance, but one that actually acts on real account data. It exposes six tools: real-time fraud risk scoring (analyzes a transaction against the account's actual spend history — amount, location, velocity, merchant pattern — and returns a fraud probability with a concrete next-action plan), CIBIL score lookup, personal loan eligibility (explains exactly why a loan is approved or rejected and lists the documents needed — aligned with RBI's Digital Lending Guidelines on rejection transparency), SME business loan assessment (turnover, GST compliance, years in operation), insurance claim investigation (flags early claims, high-value claims, and repeat-claimant patterns), and personalized financial advice (turns income/debt data into a concrete monthly savings and investment plan). It also pulls live market data via Alpha Vantage as a real external data signal. Every tool result renders as a polished visual widget inside the AI chat itself — risk gauges, eligibility cards, CIBIL score dials — with one-click PDF/Word export for compliance record-keeping. Who it's for: banks, NBFCs, and fintechs that want to give an AI assistant safe, auditable access to lending and fraud decisions without exposing raw databases — the AI only ever sees what a tool explicitly returns. What makes it special: because it's built on MCP rather than a one-off API, the exact same server works unmodified inside Claude, ChatGPT, or any future MCP-compatible banking assistant — one build, many front doors. Every decision is explainable, since a resource exposes the underlying rulebook, so an examiner can ask why a decision was made and get the exact rule that fired — not a black box.
Who built CredEdge — an MCP server that turns AI into a real bank employee for fraud, credit & lending?
CredEdge — an MCP server that turns AI into a real bank employee for fraud, credit & lending was built by team Gojo Protocol🔥 at the Amrita University Amritapuri campus NitroStack × MCP To The Moon hackathon, in the BFSI & FinTech 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.