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MCPg - Production-grade PostgreSQL MCP Server

MCPg - Production-grade PostgreSQL MCP Server

by devopam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

List domains

list_domains
Read-only

Inspect PostgreSQL domain types in a schema to view base types, nullability, defaults, and CHECK constraints for accurate schema analysis.

Instructions

List the domain types in a schema, with base type, default, and check constraints. Returns a list of objects with name, base_type, nullable, default, and constraints (list of CHECK clauses).

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": "list_domains"
  }
}

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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds the shape of the returned rows, but says nothing about whether the schema must exist, whether an empty list is returned for unknown schemas, or how the optional secondary-database targeting affects behavior — context that matters given the schema's note that unconfigured database names are rejected.

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 compact sentences with the purpose front-loaded and no filler. The second sentence partly restates return fields that the output schema already declares, which is mild redundancy but not bloat.

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 simple two-parameter read tool with annotations and an output schema, this is nearly complete: purpose, scope, and row shape are all stated. The remaining gap is routing guidance against the many sibling list_* tools, which the description never addresses.

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 description coverage is 50%: the `database` parameter is well documented in the schema itself, while `schema` is bare. The description only implies that `schema` names the owning schema, adding little beyond the schema. The enumerated return fields are output-schema territory rather than parameter meaning.

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 specific verb and resource ("List the domain types in a schema") and enumerates the attributes surfaced (base type, default, check constraints). It is clearly distinguishable from siblings like list_enums and list_composite_types by resource name, though it never explicitly contrasts itself with them.

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?

No when-to-use or when-not-to-use guidance is given. An agent must infer on its own whether to call this versus list_enums, list_composite_types, or describe_table, and there is no mention of the prerequisite of knowing a schema name (obtainable from list_schemas) or of when to target a secondary database.

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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