AV-MCP Automator
Middleware that uses Model Context Protocol and generative AI to automatically generate native Crestron Construct interfaces (.cuig/.cuib), enabling natural language creation of AV control UI components.
README
AV-MCP Automator
Middleware basado en Model Context Protocol para la generación automática de interfaces nativas de Crestron Construct™ (.cuig / .cuib) mediante IA generativa.
Empresa: DACER S.A.C. — Miraflores, Lima, Perú
Practicante: Brayan Delgado Oblitas
Metodología: RUP adaptado (desarrollador único) — 14 semanas
Estructura del proyecto
AV-MCP_Automator/
├── docs/ # Fases RUP: Inicio y Elaboración
│ ├── 01_Inception/ # Visión, casos de uso, requisitos, riesgos, glosario
│ └── 02_Elaboration/ # DAS, esquema JSON compilador, diagramas UML
│ ├── architecture/
│ ├── schemas/
│ └── diagrams/
├── src/ # Fase RUP: Construcción
│ ├── client/ # Capa 1 — UI Streamlit
│ ├── server_mcp/ # Capa 2 — Servidor FastMCP + Compilador .cuig
│ │ ├── tools/ # search_tool, builder_tool, cuig_tool
│ │ └── templates/ # Plantillas Python por componente CH5
│ ├── core_ai/ # Capa 3 — Enrutador IA (Gemini → Ollama fallback)
│ │ ├── prompts/ # System prompts
│ │ └── schemas/ # Modelos Pydantic para validar JSON de Gemini
│ └── data_layer/ # Capa 4 — LanceDB + documentación fuente
│ ├── raw_docs/ # Docs .md de Crestron para indexar
│ └── lancedb_store/ # Base vectorial embebida (generada en runtime)
├── tests/ # Pruebas unitarias e integración
├── deploy/
│ └── manuals/ # Manual de usuario y guía de despliegue (Fase Transición)
├── .env.example # Variables de entorno requeridas
└── requirements.txt # Dependencias Python
Inicio rápido
# 1. Clonar e instalar dependencias
pip install -r requirements.txt
# 2. Configurar variables de entorno
cp .env.example .env
# Editar .env con tu clave de API de Gemini
# 3. Indexar documentación en LanceDB
python src/data_layer/ingest.py
# 4. Iniciar servidor MCP
python src/server_mcp/main.py
# 5. Iniciar UI (en otra terminal)
streamlit run src/client/app.py
Stack tecnológico
| Capa | Tecnología |
|---|---|
| UI Cliente | Streamlit (Python) |
| Servidor MCP / Compilador | FastMCP (Python) |
| IA Principal | Gemini 2.5 Flash-Lite (API) |
| IA Fallback | Ollama + Llama 3.2 3B (Q4_K_M) |
| Base Vectorial | LanceDB |
| Ecosistema destino | Crestron Construct™ (.cuig / .cuib) |
Documentación del proyecto
Ver docs/02_Elaboration/architecture/AV-MCP_Automator_Contexto_Proyecto.md
para el documento maestro de contexto del proyecto.
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