magento-sql-mcp-server

Get Largest Tables

get_largest_tables

Read-onlyIdempotent

Identify the largest Magento tables by storage size to spot bloated tables before running broad queries. Returns top N tables with sizes from INFORMATION_SCHEMA.

Instructions

Returns the biggest Magento tables by storage size (DATA + INDEX) from INFORMATION_SCHEMA. Use to find bloated tables before running broad SELECTs. Row counts are approximate for InnoDB.

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": "get_largest_tables"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Number of largest tables to return (default 20, max 100).
`profile`	No	Override the MAGENTO_SQL_PROFILE env var for this call only. Use list_connection_profiles to see available names.
`magentoRoot`	No	Absolute path to the Magento root (must contain app/etc/env.php). Defaults to MAGENTO_ROOT env var or auto-discovery.

Output Schema

Name	Required	Description	Default
`note`	No
`rows`	Yes
`sampled`	No
`rowCount`	Yes
`truncated`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.4.0Aug 25, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds a useful behavioral detail beyond annotations: 'Row counts are approximate for InnoDB.' This warns about data precision and adds value without contradicting the 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?

Two sentences, no wasted words. The primary purpose is front-loaded, and the usage guidance follows immediately. Everything is relevant and to the point.

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 read-only listing tool with no required parameters and smooth schema coverage (100% param descriptions, output schema present), the description is complete enough. It covers storage metrics and the approximate-row-count caveat. It does not mention pagination or specific RETURN format, but the output schema likely covers that.

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?

Schema description coverage is 100%, and all three parameters have detailed descriptions (limit bounds, profile override, magentoRoot path). The description itself does not add additional meaning beyond what the schema already provides, so the baseline of 3 applies.

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 states a specific verb ('Returns'), a precise resource ('biggest Magento tables by storage size'), and the source ('INFORMATION_SCHEMA'). It also clarifies the metric (DATA + INDEX), which differentiates it from siblings like list_tables or get_heavy_log_tables that might focus on other criteria.

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?

The second sentence gives a clear when-to-use: 'Use to find bloated tables before running broad SELECTs.' This is actionable context. However, it does not mention any alternatives or explicitly state when not to use it, which would push to a 5.

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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