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Teradata

Teradata MCP Server

Official
by Teradata

base_columnDescription

Retrieves column details for any table or view in Teradata, with optional filtering by database and table name and support for materializing results.

Instructions

Shows detailed column information about a database table or view.

Arguments: database_name - Database name. Defaults to '%' (all databases). obj_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
database_nameNoDatabase name. Defaults to '%' (all databases).%
obj_nameNoTable or view name. Defaults to '%' (all tables).%
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It reveals a key behavioral trait: materializing results as a volatile table when persist=True. However, it does not disclose other potential side effects, authentication needs, or rate limits.

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 concise with a clear purpose statement followed by bulleted arguments. It is well-structured but could be slightly more streamlined.

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

Completeness2/5

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

The description lacks explanation of return values (no output schema) and does not differentiate from similar sibling tools. For a tool with no output schema, more detail on what 'detailed column information' entails is needed.

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?

Input schema coverage is 100%, so parameters are already well-documented. The description restates the parameter meanings without adding significant new semantic insight beyond the schema. Baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool shows detailed column information about a database table or view, using specific verb and resource. However, it does not differentiate from sibling tool 'base_columnMetadata', which likely serves a similar purpose.

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

Usage Guidelines2/5

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

The description lists arguments with defaults but provides no guidance on when to use this tool versus its siblings or alternatives. No 'when-not-to-use' or context for selection.

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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