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MCPg - Production-grade PostgreSQL MCP Server

Get compact schema

get_compact_schema
Read-only

Retrieve a token-efficient summary of a database schema including tables, columns, primary keys, nullability, and relations to minimize context usage.

Instructions

Return a highly condensed, token-efficient text summary of a schema's tables, columns, primary keys, nullability, and relations to save context window tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description need not reiterate safety. It adds context by detailing what the summary includes (columns, keys, relations), going beyond the annotation. No side effects are mentioned, but for a read-only operation that is acceptable.

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?

A single, well-structured sentence that conveys the tool's core value without waste. Every phrase serves a purpose, and the token-efficiency angle is front-loaded.

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 presence of an output schema and annotations, the description adequately covers the return content and purpose. It could mention the output format (text), but for a compact summary tool this is minor. Overall sufficient for the task.

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 low (50%), and the description provides no additional meaning for the parameters. The 'schema' parameter is required but not mentioned in the description, leaving the agent to rely solely on the name. The optional 'database' parameter is briefly described in the schema, but the description fails to explain how to use either.

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 returns a 'highly condensed, token-efficient text summary' of a schema's specifics (tables, columns, keys, relations). This distinctively separates it from sibling tools like 'get_database_ddl' (full DDL) or 'generate_schema_diagram' (visual).

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 use by mentioning token savings, but it does not explicitly state when to use this tool over alternatives or provide when-not-to-use guidance. The agent can infer from sibling names, but the description itself lacks direct usage direction.

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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