DRIP

DRIP

AI-powered emergency coordination platform built with NitroStack MCP to accelerate disaster response through intelligent planning, resource orchestration, and real-time operational insights.

Category
Visit Server

README

DRIP – Disaster Response Intelligence Platform

AI-powered emergency coordination platform built with NitroStack MCP to accelerate disaster response through intelligent planning, resource orchestration, and real-time operational insights.

Overview

DRIP (Disaster Response Intelligence Platform) is an AI-driven emergency response system designed to assist Disaster Management Authorities, Emergency Operations Centers (EOCs), first responders, and relief organizations.

Instead of relying on fragmented information and manual coordination, DRIP orchestrates specialized intelligence modules to:

  • Assess disaster severity
  • Analyze environmental conditions
  • Locate critical resources
  • Coordinate rescue operations
  • Generate actionable Situation Reports for decision makers

Built using NitroStack MCP, DRIP exposes intelligent tools that can be orchestrated by AI agents to support emergency response workflows.


Features

AI Planner

  • Intelligent incident analysis
  • Dynamic task selection
  • LLM-powered Situation Report generation
  • Minimal task execution strategy
  • Hallucination-resistant reporting

Intelligence Module

Provides:

  • Weather assessment
  • Hazard analysis
  • Safe route identification
  • Nearest hospital discovery
  • Shelter discovery
  • Severity estimation

Operations Module

Coordinates operational response:

  • Incident reporting
  • Rescue vehicle allocation
  • Volunteer assignment
  • Shelter updates
  • Relief inventory management
  • Emergency deployment workflow

Situation Reports

Automatically generates structured operational reports including:

  • Executive Summary
  • Severity Assessment
  • Affected Area
  • Threat Analysis
  • Resource Status
  • Tactical Action Plan
  • Intelligence Gaps
  • Operational Rationale

Architecture

                    User Incident
                          │
                          ▼
                 Planner Orchestrator
                          │
          ┌───────────────┼───────────────┐
          ▼               ▼               ▼
   Intelligence     Resources      Operations
          │               │               │
          └───────────────┼───────────────┘
                          ▼
               AI Situation Report

Built With

  • NitroStack MCP
  • TypeScript
  • Node.js
  • NitroCloud
  • Gemini API
  • Zod
  • Mapbox (Widgets)

Project Structure

src
│
├── planner/
│   ├── planner.module.ts
│   ├── planner.service.ts
│   └── planner.tasks.ts
│
├── modules/
│   ├── intelligence/
│   ├── operations/
│   ├── resources/
│   └── pizzaz/
│
├── prompts/
│   ├── systemPrompt.ts
│   └── responsePrompt.ts
│
├── services/
│   └── llm.ts
│
└── app.module.ts

Running Locally

git clone https://github.com/nanzz-leo/DRIP.git

cd DRIP

npm install

npm run build

npm run dev

Example Workflow

Incident Report
        │
        ▼
Planner analyzes incident
        │
        ▼
Assess Disaster
        │
        ▼
Locate Resources
        │
        ▼
Plan Rescue
        │
        ▼
Generate AI Situation Report

Design Principles

  • Human life first
  • Verified information only
  • Zero hallucination policy
  • Modular AI orchestration
  • MCP-native architecture
  • Extensible task-based design

Team

Built during the NitroStack × Amrita University Hackathon.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured