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girish-krishna-aem/aem.mcp

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AEM MCP Poc

개요

A proof-of-concept for lightning detection and weather warning, built on the Model Context Protocol (MCP). Ask a plain-English question like "Is there lightning near Germantown MD within 50 miles?" and get a structured answer — no API wrangling required. 📍 This is Phase 1 of a 3-phase roadmap. See Roadmap for what's real today vs. planned. Most "lightning detection" demos either hardcode a handful of cities or require you to already know latitude/longitude. This project exists to show a for a natural-language weather-safety assistant: - A user (or another AI agent) asks a question in plain English. - A lightweight figures out what is being asked and what information it needs. - If the question mentions a place — a city, a ZIP code, or a full street address — the Coordinator resolves it to real coordinates using (no API key, no cost). - The Coordinator then calls a dedicated over the real MCP protocol (not a shortcut function call) to get the answer.

README

원문 README의 일부입니다. 원문 보기.

⚡ Lightning Detection MCP — Server & Coordinator Agent

A proof-of-concept multi-agent system for lightning detection and weather warning, built on the Model Context Protocol (MCP). Ask a plain-English question like “Is there lightning near Germantown MD within 50 miles?” and get a structured answer — no API wrangling required.

📍 This is Phase 1 of a 3-phase roadmap. See Roadmap for what’s real today vs. planned.


🎯 What is this?

Most “lightning detection” demos either hardcode a handful of cities or require you to already know latitude/longitude. This project exists to show a realistic, extensible pattern for a natural-language weather-safety assistant:

  • A user (or another AI agent) asks a question in plain English.
  • A lightweight Coordinator Agent figures out what is being asked and what information it needs.
  • If the question mentions a place — a city, a ZIP code, or a full street address — the Coordinator resolves it to real coordinates using free, public geocoding APIs (no API key, no cost).
  • The Coordinator then calls a dedicated Lightning MCP Server over the real MCP protocol (not a shortcut function call) to get the answer.
  • The result comes back as a clear, human-readable summary.

This mirrors a common enterprise pattern: a Coordinator/Orchestrator Agent sitting in front of one or more domain-specific MCP servers, each responsible for a narrow slice of functionality (lightning here; could be accounts, transactions, inventory, etc. in other systems).


🧩 How it fits together

flowchart LR
    User(["🧑 User'Is there lightning nearGermantown MD within 50 miles?'"])

    subgraph Coordinator["Coordinator Agent  (Unit 2)"]
        direction TB
        IC["1️⃣ Intent Classifier(strike / weather / sensor / informer)"]
        PE["2️⃣ Parameter Extractor(location, radius, sensor id, zone...)"]
        LG["3️⃣ Location Geocoder"]
        RF["5️⃣ Result Formatter"]
        IC --> PE --> LG
    end

    subgraph Geocoders["Free Public Geocoding APIs"]
        direction TB
        Census["US Census Geocoder(primary — full addresses)"]
        Nominatim["Nominatim / OpenStreetMap(fallback — city/state, ZIP)"]
        Census -- "no match" --> Nominatim
    end

    subgraph MCP["Lightning MCP Server  (Unit 1)"]
        direction TB
        Tools["4️⃣ MCP Toolsstrikes · daily/hourly/mock forecast · sensor · informer"]
    end

    User --> IC
    LG -- "resolve address → lat/lon" --> Geocoders
    LG --> RF
    PE -- "lat/lon + params" --> Tools
    Tools -- "MCP protocol (HTTP)" --> RF
    RF --> Answer(["✅ Answer'3 strikes detected, nearest 12km away'"])

    style User fill:#CE93D8,stroke:#6A1B9A,stroke-width:2px,color:#000
    style Answer fill:#CE93D8,stroke:#6A1B9A,stroke-width:2px,color:#000
    style Coordinator fill:#BBDEFB,stroke:#1565C0,stroke-width:2px,color:#000
GitHub에서 전체 README 보기

설치

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