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MySQL MCP Server

MySQL REGEXP Match

mysql_regexp_match
Read-only

Find rows in a MySQL table where a column value matches a regular expression pattern.

Instructions

Find rows where column matches a regular expression pattern.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
colNoAlias for column
sqlNoAlias for pattern
nameNoAlias for table
limitNoMaximum number of rows to return
queryNoAlias for pattern
tableNoTable name
whereNoAdditional WHERE clause for filtering
columnNoColumn name
filterNoAlias for where
patternNoRegular expression pattern
tableNameNoAlias for table

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoError code (e.g. VALIDATION_ERROR, QUERY_ERROR)
dataNo
errorNoError message if operation failed
detailsNoAdditional error context
metricsNoToken estimation metrics
successYesWhether the operation succeeded
categoryNoError category (validation, query, connection, internal)
suggestionNoSuggested fix for the error
recoverableNoWhether the error is recoverable
Behavior2/5

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

Beyond the annotations (readOnlyHint), the description adds no behavioral context such as regex dialect, case sensitivity, performance considerations, or edge cases.

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?

The description is concise (one sentence) but overly terse; it could include essential details without becoming verbose, such as noting required parameters.

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?

Given 11 parameters and many optional aliases, the description lacks completeness; it does not explain how to specify table, column, and pattern, leaving the agent under-informed.

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?

Despite 100% schema coverage, the description fails to clarify the purpose of multiple aliases (e.g., col/column, table/name/tableName) or how parameters interact, which is crucial for correct invocation.

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 action (find rows) and the method (regex pattern match), distinguishing it from LIKE-based search and making its purpose immediately understandable.

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 like mysql_like_search, nor any conditions or exclusions for its use.

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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