Enterprise AI & Workplace Automation Team RageByteSubmitted August 1, 2026

COGNITIVE CONSISTENCY MCP SERVER

An MCP app on the Model Context Protocol built by Team RageByte at the SRMIST NitroStack × MCP To The Moon hackathon and deployed on NitroStack.

About this project

What it does: This MCP server gives AI agents a shared, persistent memory. When one agent (e.g., a research agent) discovers something and stores it as a memory, any other agent (e.g., a coding agent) can recall that knowledge instantly — no repeated work. How it works: Memories are stored in SQLite with 4 types: fact — something an agent learned decision — a choice an agent made (with reasoning) event — something that happened (e.g., handoff between agents) result — the final output of a completed task 7 MCP Tools exposed: Tool What it does remember Store a new memory (fact/decision/event/result) with importance score recall Search memories by keyword to find what other agents already know get_task_memory Get all memories for a task, grouped by type get_decisions Get only the decisions made on a project or task get_agent_history Get everything a specific agent has done store_result Store the final output of a completed task handoff_task Record that one agent is passing work to another Tech stack: TypeScript, NitroStack framework (@Tool decorators + Zod schemas), sql.js for SQLite storage (pure WebAssembly, no C++ build tools needed). The code is ready in the repo under nitrostack-server/. The leader needs to either pull it and copy the files from nitrostack-server/src/modules/memory/ into their existing src/ folder, or use nitrostack-server/ as a standalone project.

Enterprise AI & Workplace Automation track

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

Team Team RageByte

  • B. MURALI DHARANLead

  • Sridevi R

  • VALAVAN K P

  • Jahadeep Sundar S

Frequently asked questions

What does COGNITIVE CONSISTENCY MCP SERVER do?
What it does: This MCP server gives AI agents a shared, persistent memory. When one agent (e.g., a research agent) discovers something and stores it as a memory, any other agent (e.g., a coding agent) can recall that knowledge instantly — no repeated work. How it works: Memories are stored in SQLite with 4 types: fact — something an agent learned decision — a choice an agent made (with reasoning) event — something that happened (e.g., handoff between agents) result — the final output of a completed task 7 MCP Tools exposed: Tool What it does remember Store a new memory (fact/decision/event/result) with importance score recall Search memories by keyword to find what other agents already know get_task_memory Get all memories for a task, grouped by type get_decisions Get only the decisions made on a project or task get_agent_history Get everything a specific agent has done store_result Store the final output of a completed task handoff_task Record that one agent is passing work to another Tech stack: TypeScript, NitroStack framework (@Tool decorators + Zod schemas), sql.js for SQLite storage (pure WebAssembly, no C++ build tools needed). The code is ready in the repo under nitrostack-server/. The leader needs to either pull it and copy the files from nitrostack-server/src/modules/memory/ into their existing src/ folder, or use nitrostack-server/ as a standalone project.
Who built COGNITIVE CONSISTENCY MCP SERVER?
COGNITIVE CONSISTENCY MCP SERVER was built by team Team RageByte at the SRMIST 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.