PostgreSQL MCP Server

Get PostgreSQL Server Information

pg_server_info

Read-onlyIdempotent

Retrieve detailed PostgreSQL server information including version, connection details, memory settings, WAL configuration, and runtime parameters. Supports JSON or Markdown output.

Instructions

Get detailed PostgreSQL server information: version, connection details, memory settings, WAL configuration, and runtime parameters.

Returns: JSON: { version, current_database, current_user, settings: {...}, uptime } Markdown: formatted multi-section report

Useful for understanding the server environment, verifying connection details, and checking key configuration values.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pg_server_info"
  }
}

Input Schema

Name	Required	Description	Default
`response_format`	No	Output format: 'markdown' for human-readable, 'json' for machine-readable	markdown

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 18, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds value by detailing the return structure (version, current_database, current_user, settings, uptime) and format options (JSON or Markdown), going beyond what annotations provide.

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 is three sentences, efficiently structured: first sentence states purpose, second lists return types, third gives use case context. No wasteful words, front-loaded with key information.

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

Completeness5/5

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

Given the tool has low complexity (one optional parameter), rich annotations, and no output schema, the description adequately covers what the tool returns, output format options, and use cases. It is complete for an informational tool.

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% with one parameter (response_format) fully described via enum and default. The description mentions output formats but does not add significant meaning beyond the schema, so baseline score of 3 is appropriate.

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 it retrieves detailed PostgreSQL server information including version, connection details, memory settings, WAL configuration, and runtime parameters. This specific verb+resource combination distinguishes it from siblings like pg_list_settings (which lists individual settings) and pg_connection_stats (focused on connection statistics).

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

Usage Guidelines4/5

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

The description provides clear usage context: 'Useful for understanding the server environment, verifying connection details, and checking key configuration values.' However, it does not explicitly state when not to use this tool or suggest alternatives, which would strengthen the guidance.

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