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Teradata MCP Server

Official
by Teradata

base_tablePreview

Preview data samples and infer table structure from Teradata databases using SQLAlchemy. Provides fully rendered SQL and metadata for analysis and query validation.

Instructions

This function returns data sample and inferred structure from a database table or view via SQLAlchemy, bind parameters if provided (prepared SQL), and return the fully rendered SQL (with literals) in metadata.

Arguments: table_name - table or view name database_name - Database name

Returns: ResponseType: formatted response with query results + metadata

Input Schema

NameRequiredDescriptionDefault
database_nameNo
table_nameYes

Input Schema (JSON Schema)

{ "properties": { "database_name": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "title": "Database Name" }, "table_name": { "title": "Table Name", "type": "string" } }, "required": [ "table_name" ], "title": "handle_base_tablePreviewArguments", "type": "object" }

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Teradata/teradata-mcp-server'

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