fix: полная синхронизация схемы БД с реальными колонками и enum-ами ...

- Убраны несуществующие колонки: floors_count, layout_type, metro_distance_meters, embedding, search_vector

- Добавлены реальные колонки: floors_total, layout, metro_distance_min, street, bedrooms_count, bathrooms_count, и др.

- Исправлены enum значения: renovation_status, window_view, heating_type, bathroom_type, parking_type, metro_distance_type

- Обновлены MetadataFilters, ListingResult, describe_schema, _build_where_clause

fix: remove layout_type from USER_COLUMNS and schema description — column absent in real DB ...

Same fix pattern as floors_count.

fix: remove floors_count from USER_COLUMNS — DB schema mismatch ...

Real database vmk_data does not have 'floors_count' column.
This was causing asyncpg.PostgresError on every SELECT that included
floors_count in _SELECT_COLUMNS built from USER_COLUMNS.

Removed from:
- db.py USER_COLUMNS (no longer included in SELECT)
- tools.py describe_schema JSON schema docs

ListingResult.floors_count kept as int|None=None for backward compatibility
with future schema additions — Pydantic safely defaults to None when column
is absent from query result.

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>