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MCPg - Production-grade PostgreSQL MCP Server

Get WarehousePG status

get_warehousepg_status
Read-only

Check if the database is a WarehousePG or Greenplum MPP cluster, returning availability, coordinator role, primary segment count, and mirroring status. Returns diagnostic for non-WarehousePG servers.

Instructions

Probe the connected server for the WarehousePG (Greenplum-derived MPP) signature. Reports available=true only when BOTH the version string mentions WarehousePG / Greenplum AND the gp_segment_configuration catalog view exists. Surfaces coordinator_role, segment_count (primary segments only), and mirroring (bool). On vanilla PostgreSQL clusters returns available=false with a clean diagnostic — the rest of the mcpg.warehousepg.* family advertise themselves inert via this probe. Read-only; never raises.

Example: get_warehousepg_status()

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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailYes
versionYes
availableYes
mirroringYes
segment_countYes
coordinator_roleYes
Behavior4/5

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

The description adds value beyond annotations by detailing the probe conditions (version string and catalog view), output fields (coordinator_role, segment_count, mirroring), and behavior ('never raises'). Annotations provide readOnlyHint and openWorldHint, which are consistent.

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 concise, well-structured, and front-loaded with the purpose. Every sentence adds value, and it includes an example call. No wasted words.

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?

Given the tool's simple probe behavior and existence of an output schema, the description sufficiently covers what the agent needs: purpose, conditions, return fields, and read-only nature. It also references sibling tools in the family.

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 100% with the single optional parameter well-documented in the schema. The description adds no additional parameter information beyond what the schema already provides, so baseline 3 is appropriate.

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?

The description clearly states the tool probes for WarehousePG/Greenplum signature and explains conditions for available=true. It is specific to the resource, but does not explicitly distinguish from sibling status tools like get_aio_status or get_pgq_status, missing the highest tier.

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 for checking WarehousePG availability and mentions read-only nature, but does not explicitly state when to use this tool vs alternatives or provide exclusions. The optional database parameter is explained with a reference to list_databases.

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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