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MCPg - Production-grade PostgreSQL MCP Server

List resource groups

list_resource_groups
Read-only

Lists configured resource groups with concurrency, CPU, memory limits, and live running or queued queries. Read-only; returns available=false on vanilla PG.

Instructions

List configured WarehousePG resource groups + their utilisation. Reads gp_toolkit.gp_resgroup_status for concurrency, cpu_max_percent, cpu_weight, memory_limit, memory_shared_quota, plus live num_running / num_queueing. Pairs with analyze_workload for 'where's my workload time going' diagnosis. Read-only. On vanilla PG returns available=false.

Example: list_resource_groups()

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
groupsYes
availableYes
Behavior4/5

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

Annotations already declare readOnlyHint=true; description reinforces read-only and adds specifics: reads from gp_toolkit.gp_resgroup_status, lists returned fields, and notes that on vanilla PG it returns available=false. This adds value beyond 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?

Three sentences: first states purpose and source, second adds context, third gives example. Front-loaded with core info, no redundant words. Every sentence serves a purpose.

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 output schema exists, description doesn't need to detail return format. Covers source, fields, vanilla PG behavior, and pairing. Could mention permission requirements or error scenarios, but for a simple list tool it is sufficiently complete.

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?

Only one optional parameter 'database' with schema description. Description adds cross-reference hint to list_databases for configured ids, but does not elaborate on format or constraints. Schema coverage is 100%, so baseline is 3; this is adequate.

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?

Clearly states it lists resource groups, specifies the source view (gp_toolkit.gp_resgroup_status), enumerates returned fields (concurrency, cpu_max_percent, etc.), and distinguishes behavior on vanilla PG. Differentiates from sibling tools by naming a complementary tool (analyze_workload).

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?

Provides context for usage: pairs with analyze_workload for workload diagnosis. Mentions read-only nature and fallback on vanilla PG, implying when the tool is applicable. Could explicitly state when not to use, but the pairing and caveat provide good guidance.

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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