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sql-query-mcp

sql-query-mcp

by andyWang1688
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_schemas

List all visible schemas in a PostgreSQL database using a connection ID.

Instructions

List visible schemas for a PostgreSQL connection.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "connection_id": "<connection_id>"
    },
    "name": "list_schemas"
  }
}

Input Schema

NameRequiredDescriptionDefault
connection_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0
  2. Removedv0.1.2
  3. First observedv0.1.3

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are present, so the description must fully disclose behavioral traits. It only says 'list visible schemas' and omits other traits like mutability, safety, or permissions. This is insufficient for an agent to understand implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at 6 words, which is efficient for a simple list tool. However, it lacks structure that could include parameter context or usage notes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple nature of the tool and lack of output schema, the description provides minimal context about what the list contains or how filtering ('visible') works. It is adequate but not thorough for robust tool selection.

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?

With 0% schema description coverage, the description should clarify the single required parameter connection_id. It only vaguely refers to 'a PostgreSQL connection' without adding meaning beyond the schema's name and type.

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 lists visible schemas for a PostgreSQL connection, which distinguishes it from siblings like list_tables and list_databases that list different objects.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor any conditions or exclusions. The agent is left to infer usage context from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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