AuraAssist
Allows generating VLM scene descriptions via Amazon Bedrock, optionally using AWS credentials; Bedrock is mocked by default.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AuraAssistturn off the kitchen lights and start my bedtime routine"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AuraAssist
A context-aware, hands-free home companion for the Amazon Alexa+ track. Built as a self-hosted MCP server (Streamable HTTP, MCP 2025-11-25+) with a web-based simulator that acts as an MCP client.
Features
Streamable HTTP MCP server at
/mcpwith tools:get_home_snapshot,describe_scene,find_object,get_recent_events,run_routine,control_device,generate_daily_briefing,set_user_preferenceRoutine orchestrator with confirmation flow (
bedtime,leaving_home,morning)Event memory (SQLite) and home-state model with mock devices
VLM scene description via Amazon Bedrock (mocked by default)
Privacy-first: no face ID, structured JSON, confirmations for sensitive actions
Minimal web simulator (Vite + React + TS) to call MCP tools and visualize state
Related MCP server: mcp-ha
Quick Start
1) Install Python deps
cd C:/Users/DELL/Desktop/MCP_SERVER/aura-assist
pip install -r requirements.txt2) Run MCP server
uvicorn server.main:app --host 127.0.0.1 --port 8000 --reloadServer: http://127.0.0.1:8000/, MCP endpoint: http://127.0.0.1:8000/mcp
3) Run web simulator
cd web
npm i
npm run devMCP Testing
Use MCP Inspector or curl:
List tools:
POST /mcpwith initialize + tools/list (Streamable HTTP)Call
run_routinewith {"routine_name":"bedtime","confirm":false} first, then confirm:true
Environment
Copy .env.example to .env and set AWS keys to use real Bedrock (optional).
License
MIT
This server cannot be deployed
Maintenance
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