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sql-mcp

sql-mcp

by hogiabao2601
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_tables

Read-only

Lists database tables with type, engine, approximate row count, and size in MB, helping you identify large tables before querying them.

Instructions

List tables of a database with type, engine, APPROXIMATE row count, and size in MB. Use it to find the big tables before querying them.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
schemaNo
profileNo
databaseNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds one genuinely useful caveat — the row count is APPROXIMATE — which prevents an agent treating it as exact, but says nothing about permissions, latency, or what happens when schema/database are omitted.

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?

Two sentences, no waste, with the returned-field summary first and the usage hint second. Nothing could be cut without losing information.

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?

A read-only listing tool with no output schema needs little, and the return fields are summarized. However, with three undocumented optional parameters there is a meaningful gap an agent must guess around when targeting a specific schema, profile, or database.

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 0% and all three parameters (schema, profile, database) are undocumented nullable strings with null defaults. The description never mentions them, so an agent gets no guidance on what profile means or whether omitting schema/database falls back to connection defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb (list) and resource (tables of a database), plus the exact fields returned (type, engine, APPROXIMATE row count, size in MB), which clearly separates it from list_databases and describe_table. It stops short of naming a sibling alternative, so a 4 rather than a 5.

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?

"Use it to find the big tables before querying them" gives a concrete use case and sequencing hint relative to execute_query. It offers no explicit when-not or mention of search_schema/describe_table as alternatives, so no exclusions are stated.

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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