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hydrolix

mcp-hydrolix

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list_tables

Retrieve and list Hydrolix tables within a specified database to explore schema and streamline data query processes for LLM-based workflows.

Instructions

List available Hydrolix tables in a database

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseYes
likeNo

Implementation Reference

  • The primary handler for the 'list_tables' tool. Decorated with @mcp.tool() for registration in FastMCP. Executes queries against system.tables and system.columns to fetch comprehensive table information including metadata and column details.
    @mcp.tool() def list_tables(database: str, like: Optional[str] = None, not_like: Optional[str] = None): """List available Hydrolix tables in a database, including schema, comment, row count, and column count.""" logger.info(f"Listing tables in database '{database}'") client = create_hydrolix_client(get_request_credential()) query = f"SELECT database, name, engine, create_table_query, dependencies_database, dependencies_table, engine_full, sorting_key, primary_key, total_rows, total_bytes, total_bytes_uncompressed, parts, active_parts, total_marks, comment FROM system.tables WHERE database = {format_query_value(database)}" if like: query += f" AND name LIKE {format_query_value(like)}" if not_like: query += f" AND name NOT LIKE {format_query_value(not_like)}" result = client.query(query) # Deserialize result as Table dataclass instances tables = result_to_table(result.column_names, result.result_rows) for table in tables: column_data_query = f"SELECT database, table, name, type AS column_type, default_kind, default_expression, comment FROM system.columns WHERE database = {format_query_value(database)} AND table = {format_query_value(table.name)}" column_data_query_result = client.query(column_data_query) table.columns = [ c for c in result_to_column( column_data_query_result.column_names, column_data_query_result.result_rows, ) ] logger.info(f"Found {len(tables)} tables") return [asdict(table) for table in tables]
  • Dataclass defining the structure for table metadata returned by list_tables, used for output schema.
    class Table: database: str name: str engine: str create_table_query: str dependencies_database: str dependencies_table: str engine_full: str sorting_key: str primary_key: str total_rows: int total_bytes: int total_bytes_uncompressed: int parts: int active_parts: int total_marks: int comment: Optional[str] = None columns: List[Column] = field(default_factory=list)
  • Dataclass defining the structure for column metadata nested within Table objects.
    @dataclass class Column: database: str table: str name: str column_type: str default_kind: Optional[str] default_expression: Optional[str] comment: Optional[str]
  • Helper function to convert query results into List[Table] instances.
    def result_to_table(query_columns, result) -> List[Table]: return [Table(**dict(zip(query_columns, row))) for row in result]
  • Helper function to convert query results into List[Column] instances.
    def result_to_column(query_columns, result) -> List[Column]: return [Column(**dict(zip(query_columns, row))) for row in result]

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