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MCPg - Production-grade PostgreSQL MCP Server

Get database DDL

get_database_ddl
Read-only

Retrieve the CREATE DATABASE DDL for a specified database using PostgreSQL 19's pg_get_databasedef function. Returns whether the database exists and its DDL.

Instructions

Return the CREATE DATABASE DDL for a named database using PG 19's pg_get_databasedef(oid) function. Returns found=false with an empty ddl when the database doesn't exist. Requires PG 19+. Returns an object with object_type ('database'), object_name, found, and ddl.

Example: get_database_ddl(database_name='analytics')

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ddlYes
foundYes
object_nameYes
object_typeYes
Behavior4/5

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

Annotations already indicate read-only and closed world. The description adds valuable context: it uses PG 19's pg_get_databasedef function, returns a specific object structure, and handles missing databases by setting 'found=false'. This goes beyond the annotations without contradicting them.

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 plus an example, with no wasted words. It front-loads the main action and clearly explains behavior and return format. Each sentence adds value.

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?

With an output schema present, the description need not detail return values but still summarizes them. It covers the not-found case and PG version requirement. For a simple DDL retrieval tool, this is comprehensive; it lacks only optional details like error handling or permissions.

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 50% because only the 'database' parameter has a description. The description provides an example using database_name but does not explain the 'database' parameter or add meaning to 'database_name' beyond the schema. The example helps but does not fully compensate for the missing schema descriptions.

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 the tool returns 'CREATE DATABASE DDL for a named database', specifying the verb 'Return' and the resource 'DDL'. It distinguishes itself from sibling tools like get_role_ddl and get_tablespace_ddl by focusing on database DDL.

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?

The description implies usage by stating it requires PG 19+ and returns 'found=false' for non-existent databases, but it does not explicitly compare to alternatives or provide when-to-use/when-not-to-use guidance. No exclusions or sibling comparisons are mentioned.

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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