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MCPg - Production-grade PostgreSQL MCP Server

MCPg - Production-grade PostgreSQL MCP Server

by devopam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Generate sqlc schema

generate_sqlc_schema
Read-only

Convert a PostgreSQL schema into a sqlc-friendly schema.sql of plain DDL, ordered so foreign keys 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. Schema/table/column names must be plain identifiers ([A-Za-z_][A-Za-z0-9_]*); delimited names (hyphens, spaces, mixed-case-only) are not supported here because they become source identifiers in generated code — use SQL tools (export_table, dump_database) for those objects. See docs/identifier-policy.md.

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": {
      "schema": "<schema>"
    },
    "name": "generate_sqlc_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
schemaYes
databaseNoOptional: a database id from list_databases, to target a configured secondary (read-only) database; omit for the primary. Database names that are not configured ids are rejected.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.8.4
    • changedInput schema / properties / database / description
      Previous value: -"Optional: target a configured secondary (read-only) database by name; omit for the primary. Call list_databases to see the configured ids."New value: +"Optional: a database id from list_databases, to target a configured secondary (read-only) database; omit for the primary. Database names that are not configured ids are rejected."
  2. First observedv0.6.8

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint=false, so the description adds real extra context: emission order, the guarantee that the file replays cleanly against an empty database, that it runs in-process without MCPG_ALLOW_SHELL, and that it returns the rendered text as a single string. The one gap is that it does not say what happens when a schema has no tables or unsupported objects beyond naming.

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?

Front-loaded with the purpose, then ordering details, then the identifier restriction and alternatives — a logical progression with no filler. It is dense and long-ish, and the trailing docs pointer is low value for an agent, but each sentence carries 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?

For a two-parameter generation tool with an output schema present, the description covers output format, deterministic ordering, replay safety, execution mode, and the unsupported-input escape hatch. An agent has everything needed to decide to call it and to predict the result.

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 coverage is only 50%: the `database` parameter is well described in the schema itself, but `schema` has no schema-level description and the tool description never states that it is the source schema name (or whether it accepts patterns). The identifier-policy sentence indirectly constrains which objects are processable, which is useful, but the core `schema` parameter's meaning is left implicit.

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 verb and resource ("Read a PostgreSQL schema and emit a sqlc-friendly schema.sql") plus the exact output artifact, which cleanly separates it from sibling generators like generate_prisma_schema or generate_drizzle_schema. The parenthetical "(plain DDL)" pins down the format without ambiguity.

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?

Gives an explicit exclusion rule with named alternatives: delimited names (hyphens, spaces, mixed-case-only) are unsupported here and the agent should use export_table or dump_database instead. There is no general when-to-use guidance relative to the other schema generators, but the routing for the failure case is concrete.

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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