describe_table
Retrieve schema information for a specific Snowflake table, including column details and data types, to understand table structure and support database operations.
Instructions
Get the schema information for a specific table
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| table_name | Yes | Fully qualified table name in the format 'database.schema.table' |
Implementation Reference
- The main handler function that parses the fully qualified table name, executes a query against INFORMATION_SCHEMA.COLUMNS to retrieve column metadata (name, default, nullable, data_type, comment), formats the output as YAML text and JSON embedded resource.
async def handle_describe_table(arguments, db, *_): if not arguments or "table_name" not in arguments: raise ValueError("Missing table_name argument") table_spec = arguments["table_name"] split_identifier = table_spec.split(".") # Parse the fully qualified table name if len(split_identifier) < 3: raise ValueError("Table name must be fully qualified as 'database.schema.table'") database_name = split_identifier[0].upper() schema_name = split_identifier[1].upper() table_name = split_identifier[2].upper() query = f""" SELECT column_name, column_default, is_nullable, data_type, comment FROM {database_name}.information_schema.columns WHERE table_schema = '{schema_name}' AND table_name = '{table_name}' """ data, data_id = await db.execute_query(query) output = { "type": "data", "data_id": data_id, "database": database_name, "schema": schema_name, "table": table_name, "data": data, } yaml_output = data_to_yaml(output) json_output = json.dumps(output) return [ types.TextContent(type="text", text=yaml_output), types.EmbeddedResource( type="resource", resource=types.TextResourceContents(uri=f"data://{data_id}", text=json_output, mimeType="application/json"), ), ] - src/mcp_snowflake_server/server.py:464-478 (registration)Registers the describe_table tool in the all_tools list, specifying name, description, input schema (requiring fully qualified table_name), and linking to the handle_describe_table handler. This tool object is then filtered and exposed via list_tools and call_tool.
Tool( name="describe_table", description="Get the schema information for a specific table", input_schema={ "type": "object", "properties": { "table_name": { "type": "string", "description": "Fully qualified table name in the format 'database.schema.table'", }, }, "required": ["table_name"], }, handler=handle_describe_table, ), - Defines the input schema for the describe_table tool: an object with a required 'table_name' string property expecting 'database.schema.table' format.
input_schema={ "type": "object", "properties": { "table_name": { "type": "string", "description": "Fully qualified table name in the format 'database.schema.table'", }, }, "required": ["table_name"], },