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Teradata

Teradata MCP Server

Official
by Teradata
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
Python
Remote

Base Columndescription

base_columnDescription
Read-onlyIdempotent

Get column names, data types, and basic attributes for a single Teradata table or view. Use to quickly inspect table structure and fields.

Instructions

List the column names, data types, and basic attributes for a single Teradata table or view. Use for straightforward questions like 'what columns does this table have?' or 'what are the fields and their types?'. For precise Teradata-specific type codes, character sets, decimal precision, index details, or bulk metadata across many objects, use base_columnMetadata instead.

Arguments: database_name - Database name. Defaults to '%' (all databases). table_name - Table or view name. Defaults to '%' (all tables). persist - If True, materializes result as a volatile table and returns table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
persistNoIf True, materializes result as a volatile table and returns table name
table_nameNoTable or view name. Defaults to '%' (all tables).%
database_nameNoDatabase name. Defaults to '%' (all databases).%

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.1
    • removedInput schema / properties / obj_name
      Removed value: -{
-  "default": "%",
-  "description": "Table or view name. Defaults to '%' (all tables).",
-  "type": "string"
-}
    • addedInput schema / properties / table_name
      Added value: +{
+  "default": "%",
+  "description": "Table or view name. Defaults to '%' (all tables).",
+  "type": "string"
+}
  2. Changed11 schema fields changedv0.2.1
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / database_name / anyOf
      Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
    • addedInput schema / properties / database_name / default
      Added value: +"%"
    • addedInput schema / properties / database_name / description
      Added value: +"Database name. Defaults to '%' (all databases)."
    • removedInput schema / properties / database_name / title
      Removed value: -"Database Name"
    • addedInput schema / properties / database_name / type
      Added value: +"string"
    • addedInput schema / properties / obj_name / default
      Added value: +"%"
    • addedInput schema / properties / obj_name / description
      Added value: +"Table or view name. Defaults to '%' (all tables)."
    • removedInput schema / properties / obj_name / title
      Removed value: -"Obj Name"
    • addedInput schema / properties / persist
      Added value: +{
+  "default": false,
+  "description": "If True, materializes result as a volatile table and returns table name",
+  "type": "boolean"
+}
    • removedInput schema / required
      Removed value: -[
-  "database_name",
-  "obj_name"
-]
  3. Changed3 schema fields changedv1.0.0
    • addedInput schema / properties / database_name / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • removedInput schema / properties / database_name / type
      Removed value: -"string"
    • removedInput schema / title
      Removed value: -"handle_base_columnDescriptionArguments"
  4. First observed

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint and idempotentHint, covering safety. The description adds context about 'basic attributes' vs 'precise Teradata-specific type codes', which is useful. However, it claims this is 'for a single Teradata table or view' while the parameters default to '%' (all databases/tables), creating an inconsistency about actual scope behavior that is not fully disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: purpose, usage examples, alternative tool, then parameter list. It is mostly concise, though the argument list duplicates schema-provided information. Still, it front-loads the core verb and resource, and every sentence serves a clear role.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only listing tool with no output schema, the description covers functionality, examples, and alternative routing. However, it does not clarify the single-table promise against the wildcard defaults, nor describe the exact return format beyond 'column names, data types, and basic attributes'. Given the lack of an output schema, a bit more detail would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description repeats the parameter descriptions already present in the schema but adds no new semantic meaning beyond what the schema provides. The wildcard defaults are documented in the schema, so no compensation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('List'), resource ('column names, data types, and basic attributes for a single Teradata table or view'), and explicitly differentiates from sibling base_columnMetadata. An agent can distinguish this tool immediately, even before looking at schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool ('Use for straightforward questions like...') and when to use the alternative ('For precise Teradata-specific type codes... use base_columnMetadata instead'). Both conditions and the sibling name are given, leaving no inference needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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