postgres-mcp

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describe_table

Read-only

Inspect columns of a PostgreSQL table or view in the public schema, returning column metadata as a JSON array for schema checks.

Instructions

Describe the columns of a table or view in the public schema.

Args: table_name: Name of the table or view.

Returns: Column metadata as a JSON array of objects.

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

Name	Required	Description	Default
`table_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered structurally. The description adds the useful scope constraint that only the public schema is inspected, but says nothing about behavior on a missing table, permissions, or output detail beyond the annotation baseline.

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 purpose sentence is front-loaded, followed by tidy Args and Returns blocks with no filler. It is slightly over-structured for a single-parameter tool, but nothing is wasted.

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?

An output schema exists, so the return shape does not need explaining, and the description still gives a one-line summary of it. For a simple introspective tool with full annotation coverage, the definition is complete apart from missing usage routing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the parameter meaning, and it does explain table_name as the name of the table or view. The public-schema scope also implies the name is unqualified. It stops short of stating an expected format or whether views in other schemas are rejected.

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?

States a specific verb ('Describe') and resource ('columns of a table or view') with the added scope constraint of the public schema. It is clearly distinguishable from list_tables and query by intent, but it never names or contrasts with those siblings explicitly.

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?

There is no when-to-use or when-not-to-use guidance, no mention of prerequisites, and no routing to alternatives such as list_tables for discovering table names first. Usage is only implied by the pair of Args/Returns blocks.

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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