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MCPg - Production-grade PostgreSQL MCP Server

Generate sqlc schema

generate_sqlc_schema
Read-only

Generates a sqlc-friendly SQL schema from a PostgreSQL database, producing ordered DDL statements that replay cleanly against an empty database.

Instructions

Read a PostgreSQL schema and emit a sqlc-friendly schema.sql (plain DDL). Order: CREATE SCHEMA, CREATE TYPE for each enum, CREATE TABLE statements (columns only), ALTER TABLE ADD CONSTRAINT (PK / unique / check / foreign key in that order), then CREATE INDEX for non-constraint indexes. The file replays cleanly against an empty database so FKs land after all referenced tables exist. In-process — no MCPG_ALLOW_SHELL needed. Returns the rendered schema.sql text as a single string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemaYes
databaseNoOptional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already mark it as read-only. The description adds value by noting 'In-process — no MCPG_ALLOW_SHELL needed' and detailing the DDL order, which informs agents about execution context and output structure.

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?

Three sentences, front-loaded with purpose, then order, then execution note and return value. No wasted words.

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?

Covers purpose, order, execution mode, and return type. Lacks information on error handling or schema existence checks, but overall sufficient for a generation tool with good annotations.

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

Parameters2/5

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

Schema coverage is 50% (only 'database' has a description). The description does not compensate for the missing 'schema' parameter description, leaving ambiguity about what value to provide.

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?

Clearly states it reads a PostgreSQL schema and emits a sqlc-friendly schema.sql, with a specific order. Distinguishes from siblings by being sqlc-specific.

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?

Implies usage for sqlc schema generation but does not explicitly guide when to use this tool vs other schema generators (e.g., generate_diesel_schema). No when-not or alternative recommendations.

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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