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udaykumar-dhokia

postgresql-mcp

create_table

Create a new PostgreSQL table by supplying a table name and a set of columns with their data types and constraints, such as primary keys and defaults.

Instructions

Create a table with custom columns.

Example: table_name = "users" columns = { "id": "SERIAL PRIMARY KEY", "name": "TEXT NOT NULL", "age": "INT", "created_at": "TIMESTAMP DEFAULT CURRENT_TIMESTAMP" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnsYes
table_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are present, so the description carries the burden of disclosing side effects. It states the create action but does not say what happens if the table already exists, whether the operation is destructive, whether permissions are needed, or whether it returns any confirmation.

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 compact and front-loaded, with the example earning its place because the schema provides no parameter documentation. No filler.

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

Completeness3/5

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

The example makes the core call pattern clear, but the description omits behavior on conflicts (table already exists), error conditions, and post-creation confirmation. Moderate complexity tool with no annotations; enough to attempt a call but not to use it reliably in edge cases.

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?

With 0% schema description coverage, the example gives concrete meaning to both parameters: table_name is a quoted string, columns maps names to SQL type definitions like 'TEXT NOT NULL'. This is valuable, though it doesn't cover edge cases or allowed syntax.

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?

States a specific action—'Create a table with custom columns'—that is clearly separate from the sibling tools (list, describe, execute SQL). The example reinforces the resource and scope.

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?

Provides no guidance on when to use create_table over execute_sql, which could also create tables. There is no mention of prerequisites or conditions where an alternative is preferred.

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

Deploy Server

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