feat: add Alembic database migration system

Implements Alembic for managing token storage database schema versions.
Migrations run automatically on startup with full backward compatibility.

**Changes:**
- Add Alembic dependency (1.14.0+) and SQLAlchemy (auto-installed)
- Create migration infrastructure in alembic/ directory
- Add initial migration (001) capturing current schema
- Modify RefreshTokenStorage.initialize() to run migrations via anyio
- Add CLI commands: db upgrade, current, history, downgrade, migrate
- Add comprehensive migration documentation

**Backward Compatibility:**
- Pre-Alembic databases automatically stamped with revision 001
- No schema changes for existing databases
- Automatic upgrade on first startup after update

**Migration Strategy:**
Three scenarios handled:
1. New database → Run migrations from scratch
2. Pre-Alembic database → Stamp with 001 (no changes)
3. Alembic-managed → Upgrade to latest

**Architecture:**
- Uses anyio.to_thread.run_sync() for structured concurrency
- Alembic env.py runs with anyio.run() in worker thread
- SQLite-friendly migration patterns documented
- No ThreadPoolExecutor needed (anyio handles it)

**CLI Usage:**
```bash
nextcloud-mcp-server db upgrade    # Upgrade to latest
nextcloud-mcp-server db current    # Show version
nextcloud-mcp-server db history    # View changelog
nextcloud-mcp-server db downgrade  # Rollback (with confirmation)
nextcloud-mcp-server db migrate "description"  # Create migration
```

**Testing:**
- All 13 webhook storage tests pass
- New/pre-Alembic database scenarios validated
- anyio integration tested

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

nextcloud_mcp_server/api/management.py

@@ -873,6 +873,12 @@ async def unified_search(request: Request) -> JSONResponse:
             result_data["chunk_index"] = result.chunk_index
             result_data["total_chunks"] = result.total_chunks
 
+            # Add chunk offsets for modal navigation
+            if result.chunk_start_offset is not None:
+                result_data["chunk_start_offset"] = result.chunk_start_offset
+            if result.chunk_end_offset is not None:
+                result_data["chunk_end_offset"] = result.chunk_end_offset
+
             formatted_results.append(result_data)
 
         response_data: dict[str, Any] = {