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list-snowflake-warehouses

Retrieve a list of available Snowflake Data Warehouses to manage resources efficiently using the Simple Snowflake MCP Server.

Instructions

List available Data Warehouses (DWH) on Snowflake.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function that implements the core logic for the 'list-snowflake-warehouses' tool. It executes the 'SHOW WAREHOUSES' SQL command using the _safe_snowflake_execute helper and formats the output as detailed JSON or a simple list of names based on the 'include_details' parameter.
    elif name == "list-snowflake-warehouses": include_details = args.get("include_details", True) query = "SHOW WAREHOUSES" result = _safe_snowflake_execute(query, "List warehouses") if result["success"]: if include_details: output = json.dumps(result["data"], indent=2, default=str) else: warehouses = [row.get("name", "") for row in result["data"]] output = "\n".join(warehouses) return [types.TextContent(type="text", text=output)] else: return [types.TextContent(type="text", text=f"Snowflake error: {result['error']}")]
  • The tool registration in the handle_list_tools() function, including the tool's description and input schema definition for JSON Schema validation.
    types.Tool( name="list-snowflake-warehouses", description="List available Data Warehouses (DWH) on Snowflake with detailed information", inputSchema={ "type": "object", "properties": { "include_details": { "type": "boolean", "default": True, "description": "Include detailed warehouse information" } }, "additionalProperties": False }, ),
  • The input schema definition for the 'list-snowflake-warehouses' tool, specifying the optional 'include_details' boolean parameter.
    inputSchema={ "type": "object", "properties": { "include_details": { "type": "boolean", "default": True, "description": "Include detailed warehouse information" } }, "additionalProperties": False }, ),
  • Supporting helper function used by the tool handler to safely connect to Snowflake, execute the query, fetch results as JSON-compatible dicts, and handle errors.
    def _safe_snowflake_execute(query: str, description: str = "Query") -> Dict[str, Any]: """ Safely execute a Snowflake query with proper error handling and logging. """ try: logger.info(f"Executing {description}: {query[:100]}...") ctx = snowflake.connector.connect(**SNOWFLAKE_CONFIG) cur = ctx.cursor() cur.execute(query) # Handle different query types if cur.description: rows = cur.fetchall() columns = [desc[0] for desc in cur.description] result = [dict(zip(columns, row)) for row in rows] else: result = {"status": "success", "rowcount": cur.rowcount} cur.close() ctx.close() logger.info(f"{description} completed successfully") return {"success": True, "data": result} except Exception as e: logger.error(f"{description} failed: {str(e)}") return {"success": False, "error": str(e), "data": None}

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