亚马逊开发者黑客马拉松2026提交 一款由人工智能驱动的家庭协调助手，能够将自然语言请求转换为结构化的多步计划，并通过模型上下文协议（MCP）可流式HTTP传输执行批准的操作。

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🌟 执行摘要

家庭管理分散在各种不同的待办事项应用、日历提醒、配送跟踪门户和精神负担之间。HomeRelay AI 提供统一指挥中心：

1. 自然语言理解： 说家用语言（“订晚餐杂货，下午5点提醒我，并检查包裹”）。
2. 显式计划生成与审批： 使用 Gemini 2.0 Flash（带 OpenAI 备用）生成经过验证的 JSON 行动计划，执行前完全透明。
3. 模型上下文协议（MCP）标准： 通过专用MCP服务器执行操作，运行于可流式HTTP传输（/mcp]），确保工具发现标准化、安全边界和模块化扩展性。
4. **实时SSE执行流：**通过服务器发送事件（SSE）实时将进度逐步回流回浏览器。

🏠 HomeRelay AI

Amazon Developer Hackathon 2026 Submission
An AI-powered household coordination assistant that converts natural-language requests into structured multi-step plans and executes approved actions through Model Context Protocol (MCP) Streamable HTTP transport.

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🌟 Executive Summary

Home management is fragmented across disparate to-do apps, calendar reminders, delivery tracking portals, and mental overhead. HomeRelay AI provides a unified command center:

1. Natural-Language Understanding: Speaks household language (“Order groceries for dinner, remind me at 5pm, and check on that package”).
2. Explicit Plan Generation & Approval: Uses Gemini 2.0 Flash (with OpenAI fallback) to produce validated JSON action plans with complete transparency before execution.
3. Model Context Protocol (MCP) Standard: Executes actions via a dedicated MCP Server operating over Streamable HTTP transport (/mcp), ensuring standardized tool discovery, security boundaries, and modular extensibility.
4. Live SSE Execution Streaming: Streams step-by-step progress back to the browser in real time via Server-Sent Events (SSE).
5. Dark Navy & Teal SaaS Interface: Crafted with a refined dark navy palette, restrained teal accents, subtle micro-animations, and full mobile responsiveness.

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🏗️ Architecture & Data Flow

sequenceDiagram
    autonumber
    actor User as Household Member
    participant UI as Next.js Dashboard (/app)
    participant API as Next.js API Routes (/api/*)
    participant AI as AI Orchestrator (Gemini 2.0)
    participant MCP as MCP Server (Streamable HTTP)
    participant DB as Supabase PostgreSQL

    User->>UI: Enters "Water the plants and set reminder for 6pm"
    UI->>API: POST /api/plan { prompt }
    API->>AI: generatePlan(prompt)
    AI-->>API: Structured Plan JSON (validated with Zod)
    API-->>UI: { plan, steps }
    UI->>User: Displays interactive Action Plan Card

    alt User Cancels
        User->>UI: Click "Cancel"
        UI-->>User: Plan dismissed, no state altered
    else User Approves
        User->>UI: Click "Approve & Execute"
        UI->>API: POST /api/approve { prompt, plan }
        loop For each Plan Step
            API->>MCP: Streamable HTTP POST /mcp (tools/call)
            MCP->>DB: Perform DB write/query (Tasks, Reminders)
            DB-->>MCP: Mutation Result
            MCP-->>API: Tool Output JSON