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MCPg - Production-grade PostgreSQL MCP Server

Describe property graph

describe_property_graph
Read-only

Retrieve the vertex and edge tables of a property graph by schema and name. Use after listing graphs to prepare a PGQ query.

Instructions

Describe one SQL/PGQ property graph by schema-qualified name. Requires PG 19+; raises an error otherwise. Useful when an agent has located a graph via list_property_graphs and needs the full membership before composing a run_pgq query. Returns an object with schema, name, vertex_tables (list of schema.table strings), and edge_tables (same shape).

Example: describe_property_graph(schema='public', name='org_chart')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
schemaYes
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
nameYes
schemaYes
edge_tablesYes
vertex_tablesYes
Behavior4/5

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

Annotations already provide `readOnlyHint` and `openWorldHint`. The description adds value by noting the PG version requirement and error behavior, plus describing the return shape (including field names).

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 focused sentences plus an example, front-loaded with purpose, no wasted words. Every sentence contributes.

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 simple tool, annotations, and output schema presence, the description covers purpose, usage context, version requirement, return format, and an example. No gaps.

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 coverage is 33% (only `database` has a description). The description does not add parameter-level meaning beyond the example, failing to compensate for low schema coverage.

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 describes a property graph by schema-qualified name, distinguishing it from `list_property_graphs` and `run_pgq` with explicit usage context.

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 description provides explicit when-to-use guidance: after `list_property_graphs` and before composing a `run_pgq` query. It includes a Prerequisite (PG 19+) but does not explicitly state when not to use.

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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