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MCPg - Production-grade PostgreSQL MCP Server

MCPg - Production-grade PostgreSQL MCP Server

by devopam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Describe AO table

describe_ao_table
Read-only

Retrieve append-optimized or columnar table storage metadata—orientation, compression type and level, block size, and checksum—while identifying regular heap tables or unavailable support.

Instructions

Describe append-optimized (AO) / append-optimized columnar (AO/CO) storage metadata for one table: row vs column orientation, compression_type, compression_level, block_size, checksum. Reads pg_appendonly. Returns is_ao=false cleanly when the table is a regular heap. Read-only. On vanilla PG returns available=false.

Example: describe_ao_table(schema='public', table='events_ao')

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>",
      "table": "<table>"
    },
    "name": "describe_ao_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes
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
is_aoYes
tableYes
detailYes
schemaYes
checksumYes
columnarYes
block_sizeYes
compression_typeYes
compression_levelYes

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

A4.1/5.0
Behavior4/5

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

Beyond the readOnlyHint annotation, the description discloses that it reads pg_appendonly, returns is_ao=false for regular heap tables, and returns available=false on vanilla PostgreSQL. These are meaningful behavioral details about data source and fallback outcomes, though permissions and output shape are left to schema/annotations.

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: it states purpose, lists returned metadata, explains fallback behavior, and ends with a single example. Every sentence contributes relevant information without repetition.

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?

Given the output schema and read-only annotation, the description provides enough context to call the tool correctly, including fallback cases for regular heaps and vanilla PostgreSQL. Minor gaps remain around parameter semantics and explicit sibling comparison, but the core behavior is well covered.

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 description coverage is only 33%, and the description does not compensate by explaining the schema and table parameters beyond a minimal example. The optional database parameter is described in the schema, not the tool description, so parameter meaning is largely left to structured fields.

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 names a specific verb and resource: describing append-optimized storage metadata for one table. It lists the concrete metadata fields and clearly distinguishes this from a generic table description by focusing on AO/AOCO orientation and compression details.

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?

The usage context is clear: call this when you need AO/AOCO storage metadata for a specific table, and the example shows the required schema/table combination. It does not explicitly compare against sibling tools such as describe_table, but the AO-specific scope makes the intended use evident.

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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