feat: хостинг изображений объявлений и ссылки в результатах ...

- Добавлен IMAGE_STORAGE_PATH, IMAGE_BASE_URL, MAX_IMAGES_IN_SEARCH в конфиг
- Добавлена модель ListingImage и поле images в ListingResult
- Новый модуль images.py: безопасное разрешение путей, построение URL, batch-загрузка из БД
- HTTP-маршрут /images/{image_path:path} через @mcp.custom_route для раздачи файлов
- search_similar_listings, search_by_metadata и get_listing_by_id возвращают image URLs
- Обновлены README, .env.example, describe_schema, SERVER_INSTRUCTIONS, тесты
- ruff clean, pytest 15 passed

Co-Authored-By: Claude <noreply@anthropic.com>

fix: DATABASE_URL и документация — порт 5433 вместо 5432 ...

- .env: localhost:5433 (Docker пробрасывает порт 5433 на хост)

- .env.example: синхронизирован с .env

- README.md: исправлены порты, убраны старые колонки floors_count/layout_type/metro_distance_meters

- README.md: добавлены новые колонки floors_total/layout/metro_distance_min

- docker-compose.yml: уже был правильный host.docker.internal:5433

docs(README): clarify startup, config, and DB requirements ...

- Add step-by-step local and Docker launch instructions
- Expand Configuration section with required vs optional vars
- Add new 'Требования к базе данных' section:
  - Required PostgreSQL extensions (vector, pg_trgm)
  - Full property_listings column reference table
  - SQL for creating HNSW and GIN indexes
  - SQL for generating search_vector as stored tsvector
  - SQL hints for populating embedding column

Co-Authored-By: Claude <noreply@anthropic.com>

docs: comprehensive README + API reference + architecture guide ...

- Rewrite README.md with full feature list, data model, deployment,
  security, troubleshooting
- Add docs/API.md with JSON schemas, request/response examples,
  and 3 real-world usage scenarios
- Add docs/ARCHITECTURE.md with component diagram, data flows,
  DB index rationale, defense-in-depth security, scaling notes

Co-Authored-By: Claude <noreply@anthropic.com>

feat: implement MCP server for real estate database search ...

Add streamable-http MCP server with 4 tools:
- search_similar_listings: vector search via pgvector+HNSW (cosine)
- search_by_metadata: full-text search via FTS (ukrainian config)+GIN
- get_listing_by_id: fetch single listing by ID
- describe_schema: static schema documentation for AI agent

Features:
- asyncpg read-only pool with default_transaction_read_only
- parameterized queries + query safety check (multi-statement block)
- Pydantic models for input validation and JSON serialization
- Ollama nomic-embed-text client with dimension validation
- Error handling: Ollama/DB/validation exceptions wrapped in JSON
- Docker & docker-compose support
- ruff clean + 8 pytest tests passing

Co-Authored-By: Claude <noreply@anthropic.com>

Initial commit