MCP(모델 컨텍스트 프로토콜)를 사용하여 효율적인 엔터티 발견을 위해 전통적인 방법에 비해 95%의 토큰 감소를 달성한 홈 어시스턴트 대화 에이전트입니다. LM Studio, llama.cpp, Ollama, OpenAI, Google Gemini, Anthropic Claude, OpenRouter와 호환됩니다.

주요 특징

• ✅ 95% 토큰 감소: 모든 엔티티를 전송하는 대신 동적 엔터티 발견을 위해 MCP 도구를 사용합니다
• ✅ 엔터티 덤프 없음: 12,000+ 토큰 엔터티 리스트를 LLM에 절대 전송하지 않음
• ✅ 스마트 엔터티 인덱스: 컨텍스트 인식 쿼리를 위한 사전 생성된 시스템 구조 인덱스(~400-800 토큰)
• ✅ 멀티플랫폼 지원: LM Studio, llama.cpp, Ollama, OpenAI, Google Gemini, Anthropic Claude, OpenRouter에서 작동함
• ✅ 다국어 지원: 21개 언어, 현지화된 UI, 시스템 프롬프트, 음성 감지 기능
• ✅ 다중 대화: 대화 맥락과 역사를 유지함
• ✅ 동적 발견: 영역, 유형, device_class, 주, 또는 이름별로 필요에 따라 엔터티를 찾습니다
• ✅ 웹 검색 도구: 최신 정보를 위한 선택적 DuckDuckGo 또는 Brave Search 통합
• ✅ 1000+ 엔티티와 함께 작동: 대규모 홈 어시스턴트 설치에도 효율적입니다

MCP Assist for Home Assistant

A Home Assistant conversation agent that uses MCP (Model Context Protocol) for efficient entity discovery, achieving 95% token reduction compared to traditional methods. Works with LM Studio, llama.cpp, Ollama, vLLM, OpenAI (and OpenAI-compatible services), Google Gemini, Anthropic Claude, and OpenRouter, and can hand conversations to an OpenClaw or Hermes Agent gateway.

Key Features

• ✅ 95% Token Reduction: Uses MCP tools for dynamic entity discovery instead of sending all entities
• ✅ No Entity Dumps: Never sends 12,000+ token entity lists to the LLM
• ✅ Smart Entity Index: Pre-generated system structure index (~400-800 tokens) for context-aware queries
• ✅ Multi-Platform Support: Works with LM Studio, llama.cpp, Ollama, vLLM, OpenAI, Google Gemini, Anthropic Claude, and OpenRouter
• ✅ Agent Gateways: Send voice requests to an OpenClaw agent or Hermes Agent (experimental)
• ✅ Multilingual Support: 21 languages with localized UI, system prompts, and speech detection
• ✅ Multi-turn Conversations: Maintains conversation context and history
• ✅ Dynamic Discovery: Finds entities by area, type, device_class, state, or name on-demand
• ✅ Thinking Control: Turn reasoning off (or set its level) per profile for faster voice replies
• ✅ Web Search Tools: Optional DuckDuckGo, Brave Search, or SearXNG integration for current information
• ✅ Works with 1000+ Entities: Efficient even with large Home Assistant installations
• ✅ Multi-Profile Support: Run multiple conversation agents with different models

The Problem MCP Assist Solves

Traditional voice assistants send your entire entity list (lights, switches, sensors, etc.) to the LLM with every request. For a typical home with 200+ devices, this means:

• 12,000+ tokens sent every time
• Expensive API costs (cloud LLMs)
• Slow response times
• Context window limitations
• Poor performance with large homes

How MCP Assist Works

Instead of dumping all entities, MCP Assist:

1. Starts an MCP Server on Home Assistant that exposes entity discovery tools
2. Your LLM connects to the MCP server and gets access to these tools:
   • get_index - Get system structure index (areas, domains, device_classes, people, etc.)
   • discover_entities - Find entities by type, area, domain, device_class, or state
   • get_entity_details - Get current state and attributes
   • get_entity_history - Get recent state changes
   • perform_action - Control devices (only entities exposed to Assist)
   • run_script - Execute scripts and return response data
   • run_automation - Trigger automations manually
   • list_areas - List all areas in your home
   • list_domains - List all entity types
   • set_conversation_state - Smart follow-up handling
   • search / read_url - Web search and page reading (when web search is enabled)