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Northwind PostgreSQL MCP Server

Northwind PostgreSQL MCP Server

by mosesliao
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_schema

Returns a concise summary of every table and its columns, helping you understand the database structure at a glance before writing queries.

Instructions

Return a concise text summary of every table and its columns, useful for understanding the database structure at a glance.

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": "get_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden. It does disclose the output shape (concise text, all tables plus columns), but says nothing about read-only safety, size/cost on large schemas, or truncation behavior — gaps that matter for a whole-database scan. The existence of an output schema lowers the bar on return-value description.

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?

Two short lines, front-loaded with the action and result, with no filler or repetition. The trailing rationale phrase is mildly redundant with the verb 'summary' but still sets the intended use context.

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 zero-parameter read tool with an output schema, this covers what it returns and roughly why. The only missing piece is explicit routing among the closely related siblings (list_tables, describe_table), which would make it fully self-sufficient.

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?

The tool takes zero parameters, so there is no parameter meaning to convey; baseline 4 applies. The description correctly signals the no-argument nature by describing a single global summary.

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 concrete verb and resource: returns a text summary of every table and its columns. The scope (all tables, with columns) implicitly separates it from list_tables and describe_table, but no sibling is named, so an agent must infer the boundary rather than read it.

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?

"Useful for understanding the database structure at a glance" implies an orientation/overview use case, which is reasonable guidance. However, it never says when to prefer describe_table for one table's detail or list_tables for a bare table list, leaving alternative selection to inference.

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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