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lrferr

mysql-mcp-server

by lrferr

analyze_indexes

Analyze all indexes in a MySQL database to assess performance and usage, with optional filters for table, schema, or connection.

Instructions

Analisa todos os índices do banco de dados

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNameNoNome da tabela para filtrar
schemaNameNoNome do schema para filtrar
connectionNameNoNome da conexão para usar

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.5

TDQS

C2.3/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses essentially nothing. It does not say whether the operation is read-only, whether it is expensive/long-running (analyzing every index across a database is potentially heavy), what permissions it needs, or whether it mutates statistics. The word 'todos' signals a full sweep but no cost or side-effect context is given.

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

Conciseness3/5

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

It is a single short, front-loaded sentence with no padding. Conciseness is fine, but brevity here reflects under-specification rather than disciplined economy, so it sits at the minimum-viable level.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and a database-wide scope, the description is not complete enough. An agent cannot tell whether the call is safe, what it returns, or how long it takes — all of which matter for an 'analyze everything' operation.

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 filter parameters (tableName, schemaName, connectionName) are documented in the schema itself. The description adds nothing about how these filters scope the analysis (e.g. whether omitting them analyzes the entire database), so this is a baseline 3 rather than a penalty.

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

Purpose3/5

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

The description names a verb ('Analisa') and a resource ('todos os índices do banco de dados'), so it is more than a tautology. However, 'analisar' is never defined — it is unclear whether it computes statistics, checks for missing/duplicate indexes, or assesses performance — and it gives no hint of how it differs from the sibling 'get_indexes' or 'analyze_table'. Purpose is stated but vague.

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?

There is no when-to-use guidance, no prerequisite (e.g. an active connection), and no mention of the obvious alternative 'get_indexes'. An agent must infer usage entirely from the tool name.

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