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postgres-mcp-server

postgres-mcp-server

by bysonte
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TypeScript
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describe_table

Retrieve columns, indexes, and constraints of a PostgreSQL table using parameterized SQL.

Instructions

Describe columnas, índices y constraints de una tabla. Usa SQL parametrizado.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table_name": "<table_name>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
table_nameYesNombre de la tabla
schema_nameNoNombre del esquemapublic

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
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 does disclose that the tool 'Usa SQL parametrizado', which signals safe query construction, and 'describe' implies read-only behavior. However, it does not explicitly state that it makes no modifications, what privileges are required, or the exact format/shape of the returned metadata.

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

Conciseness5/5

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

The description consists of two short sentences with no filler. The primary action and target resource are front-loaded, and the note about parameterized SQL adds useful context without bloating the text.

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

Completeness4/5

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

For a simple two-parameter introspection tool, the description adequately conveys what the tool does and what it returns (column/index/constraint definitions). The lack of an output schema is somewhat mitigated by the explicit mention of the metadata types, though a bit more detail about the exact return structure would make it 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 both table_name and schema_name are already documented. The tool description adds no additional parameter-specific semantics, but the schema fully covers names and defaults, meeting the baseline.

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 uses a specific verb ('describe') and identifies the exact resource ('columnas, índices y constraints de una tabla'), making the tool's function immediately clear. It also distinguishes itself from sibling tools like list_tables and list_schemas by focusing on table structure rather than listing objects.

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

Usage Guidelines3/5

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

The tool's purpose implies when to use it, but it does not provide explicit guidance on when to prefer it over alternatives like execute_query or list_tables. There are no exclusion criteria or conditional context beyond the basic description.

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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