Panther MCP Server

IMPORTANT: This returns the table structure in Snowflake/Redshift. For writing optimal queries, ALSO call get_panther_log_type_schema() to understand: - Nested object structures (only shown as 'object' type here) - Which fields map to p_any_* indicator columns - Array element structures Example workflow: 1. get_panther_log_type_schema(["AWS.CloudTrail"]) - understand structure 2. get_table_schema("panther_logs.public", "aws_cloudtrail") - get column names/types 3. Write query using both: nested paths from log schema, column names from table schema Returns: Dict containing: - success: Boolean indicating if the query was successful - name: Table name - display_name: Table display name - description: Table description - log_type: Log type - columns: List of columns, each containing: - name: Column name - type: Column data type - description: Column description - message: Error message if unsuccessful

{ "properties": { "database_name": { "description": "The name of the database where the table is located", "example": "panther_logs.public", "title": "Database Name", "type": "string" }, "table_name": { "description": "The name of the table to get columns for", "example": "Panther.Audit", "title": "Table Name", "type": "string" } }, "required": [ "database_name", "table_name" ], "type": "object" }