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MCP Vertica

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Hybrid

get_table_structure

Retrieve table structure details including columns, data types, and constraints from Vertica databases to analyze schema information and verify database design.

Instructions

Get the structure of a table including columns, data types, and constraints.

Args:
    ctx: FastMCP context for progress reporting and logging
    table_name: Name of the table to inspect
    schema: Schema name (default: public)

Returns:
    Table structure information as a string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemaNopublic
table_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions returning 'Table structure information as a string' but does not describe the format, side effects (e.g., read-only), error behavior, or performance characteristics.

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 relatively concise, with the purpose stated in the first line. However, the Args/Returns block adds some verbosity without significant extra value, and could be 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?

Given no output schema and a potentially complex return value, the description should elaborate on the format of the returned string (e.g., JSON, plain text). It also lacks error handling details and examples.

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 0%, so the description adds value beyond the schema. It defines table_name and schema with a default, but does not provide examples, constraints (e.g., required format for table_name), or clarification of schema parameter semantics.

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 clearly states the tool retrieves table structure including columns, data types, and constraints. It uses a specific verb (Get) and resource (table structure), and is distinct from sibling tools like execute_query or list_views.

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 does not provide any guidance on when to use this tool versus alternatives. No mention of prerequisites, cases where other tools are preferred, or scope limitations.

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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