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@yawlabs/postgres-mcp

by YawLabs
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TypeScript
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Search columns by name

pg_search_columns
Read-onlyIdempotent

Find columns by name across PostgreSQL schemas using case-insensitive LIKE patterns. Use wildcards to locate which tables have a given column.

Instructions

Search for columns by name across all user schemas. Supports SQL LIKE patterns (% matches any substring, _ matches one character). Case-insensitive. Use this instead of iterating pg_describe_table when the user asks 'which tables have X'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return (default 100).
schemaNoLimit to this schema. If omitted, searches all user schemas.
patternYesLIKE pattern. Use '%' for wildcard: 'user_id', '%email%', 'created_%'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv0.12.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "rows": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "column": {
+            "type": "string"
+          },
+          "nullable": {
+            "type": "boolean"
+          },
+          "schema": {
+            "type": "string"
+          },
+          "table": {
+            "description": "Relation name; may be a view or materialized view, not only a table.",
+            "type": "string"
+          },
+          "type": {
+            "description": "Formatted type from format_type.",
+            "type": "string"
+          }
+        },
+        "required": [
+          "schema",
+          "table",
+          "column",
+          "type",
+          "nullable"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "rows"
+  ],
+  "type": "object"
+}
  2. First observedv0.7.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond annotations: LIKE semantics, case-insensitivity, and cross-schema search behavior. No contradictions with 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?

Four short sentences, each earning its place: scope, LIKE syntax, case-insensitivity, and when-to-use guidance. Front-loaded with the primary action and scoping, no filler or repetition.

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 rich annotations, a complete input schema with 100% parameter coverage, and an output schema, the description covers all essential behavioral and routing information. There is no material gap for an agent to select and invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description still adds value by clarifying that `%` is a substring wildcard, `_` matches exactly one character, and matching is case-insensitive, which goes beyond the schema's brief 'LIKE pattern' descriptions.

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?

States a specific verb ('Search'), a precise resource ('columns by name'), and a clear scope ('across all user schemas'). It distinguishes itself from pg_describe_table by naming what it is not and why it would be preferred.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells the agent when to use this tool: 'Use this instead of iterating pg_describe_table when the user asks which tables have X.' This gives a direct usage rule and names the alternative, so no inference is needed.

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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