aapanel-mcp

Tables in a database

db_tables

Read-onlyIdempotent

Lists database table names, engines, row counts, and total size so you can confirm a schema landed before pointing an app at it.

Instructions

Table names, engines, row counts and total size for a database. Use this to confirm a schema landed before pointing an app at it.

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": {
      "db_name": "<db_name>"
    },
    "name": "db_tables"
  }
}

Input Schema

Name	Required	Description	Default
`db_name`	Yes	Database name.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1-alpha.0Sep 29, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds value beyond them by listing the concrete fields returned (engines, row counts, size), which matters because there is no output schema.

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 short sentences: the first front-loads what is returned, the second gives the use case. No filler, no redundancy.

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?

For a one-parameter read-only tool with no output schema, the description supplies the essential missing piece — the returned fields and their rough shape. Minor gaps remain (behavior on a nonexistent database, whether views are included), but nothing critical for correct invocation.

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

Parameters3/5

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

Only one parameter (db_name) exists and schema coverage is 100%, so the schema fully documents it. The description implies the scope is "for a database" but adds no format, case-sensitivity, or existence semantics beyond that — the baseline 3 for full schema coverage applies.

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?

The description names the resource (a database's tables) and enumerates the specific fields returned — table names, engines, row counts, total size — so the agent knows exactly what this does. It is distinguishable in practice from siblings like db_list (databases) and db_optimize_table (mutations), though it never explicitly names those alternatives.

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 this to confirm a schema landed before pointing an app at it" gives a concrete scenario for invocation, which is more than most siblings offer. It stops short of naming alternatives or stating when not to use it (e.g. versus db_list or db_backups).

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

Deploy Server