mysql

Server Quality Checklist

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Latest release: v1.0.8
Disambiguation5/5
Each tool targets a distinct operation: reading, writing, describing schema, listing databases/tables, showing DDL, and table statistics. No ambiguity between tools.
Naming Consistency4/5
All tools share the 'mysql_' prefix and mostly follow verb_noun pattern (e.g., describe_table, list_databases). However, 'mysql_execute' and 'mysql_query' are verb-only, which slightly deviates from the pattern.
Tool Count5/5
With 7 tools, the server covers essential MySQL interactions without being bloated. Each tool serves a clear purpose, making it easy for an agent to navigate.
Completeness4/5
The set covers core CRUD, schema inspection, and metadata retrieval. DDL operations are handled via mysql_execute, so no major gaps are present. Minor missing features like server version are not critical.
Average 4.4/5 across 7 of 7 tools scored. Lowest: 3.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, destructiveHint, and idempotentHint. The description adds useful context about the output (indexes, constraints, engine settings) and the default database fallback from environment variable, which is beyond 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences and a structured args list. It front-loads the purpose. Minor room for improvement in formatting (e.g., using bullet points for args in the prose).
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?
Given no output schema, the description adequately covers the return value (complete SQL). For a simple read-only tool with two parameters, it is complete enough for an agent to understand its use. Missing error handling details is acceptable.
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 coverage is 100% with descriptions for both parameters. The description repeats the parameter info but does not add new meaning beyond what the schema already provides. The env var fallback is mentioned in both places.
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?
Clearly states the tool gets the full CREATE TABLE DDL statement, specifying the verb 'Get' and the resource. However, it does not explicitly differentiate from the sibling tool mysql_describe_table, which also provides table structure but focuses on column details rather than full DDL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving DDL statements but offers no explicit guidance on when to use this tool versus alternatives like mysql_describe_table or when to avoid it. Usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already confirm read-only, non-destructive, idempotent behavior. The description adds context about optional database with env var fallback and return format details, which enrich transparency beyond 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?
The description is concise with two sentences and a structured args/returns list, front-loading the purpose with no wasted words.
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?
The description covers purpose, parameters, and return format well for a simple tool. Lacks guidance on when to use alternatives, but otherwise complete given annotations and schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by specifying the return structure for both markdown and json formats, which is not present in the schema (no output schema).
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 'List all tables in a MySQL database,' using a specific verb and resource that distinguishes it from sibling tools like mysql_describe_table or mysql_query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing tables but does not explicitly state when to use this tool versus alternatives, such as when to use mysql_describe_table for details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, destructive, and idempotent hints. The description adds behavioral context by specifying that only databases the user has access to are returned and detailing output formats, which is valuable beyond 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?
The description is extremely concise with three short lines, each providing essential information without redundancy. It is front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema), the description sufficiently covers functionality, access scope, and return types, leaving no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'response_format' parameter fully described. The description links the parameter to output formats and shows example return structures, adding concrete meaning beyond the enum definition.
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 tool lists all databases on the MySQL server, specifically those the current user has access to, which distinguishes it from sibling tools focused on tables or queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the tool's purpose is clear, there is no explicit guidance on when to use this tool versus alternatives like mysql_list_tables, nor any when-not or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds return column fields, output format options, and database fallback behavior, giving useful context beyond 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?
Three sentences plus a list of return columns, front-loaded with purpose. Every sentence is essential and no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given comprehensive annotations, full parameter documentation, and clear return information, the description is complete for a read-only introspection tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaning by explaining the database parameter's env var fallback, response_format default, and lists return columns. Each parameter is clearly described.
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?
Description clearly states 'Get column definitions for a MySQL table' and equates to DESCRIBE/SHOW COLUMNS, distinguishing it from siblings like mysql_show_create_table (which shows CREATE TABLE) and mysql_table_stats (statistics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains parameters and default behavior for database, but does not explicitly mention when to use this tool vs alternatives. Usage is implied but not contrasted with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, and idempotent behavior. The description adds behavioral details such as the default database using MYSQL_DATABASE env var and the return format with markdown/json options. No contradictions.
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?
The description is concise: three short paragraphs covering purpose, args, and returns. No extra words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 optional parameters and no output schema, the description completely explains all parameters and the return fields (table_name, row_count, etc.). Sibling tools are distinct; no additional context needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining defaults for database and response_format, and the effect of omitting the table parameter (returns all tables).
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 'Get row count and size statistics for tables in a database,' which is a specific verb and resource. It distinguishes from sibling tools like mysql_describe_table or mysql_query, as none of those provide statistics.
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 description explains when to use the tool: to obtain table statistics. It provides context for optional parameters and defaults but does not explicitly mention alternatives or when not to use it. Sibling tool names provide implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set readOnlyHint=true and destructiveHint=false. Description adds behavioral details: only SELECT/SHOW/EXPLAIN allowed, limit defaults (100, max 1000), optional database fallback, response formats (json/markdown) with has_more flag. No contradictions.
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?
Structured into clear sections (purpose, args, returns, examples). Each sentence is informative with no redundancy. Efficiently covers all necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Thoroughly covers all 5 parameters, return formats, and edge cases (defaults, optional params). Includes examples. No output schema needed as returns are described. Complete for a read-only query tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions. Description adds examples of ? placeholders, clarifies bind parameters, and notes default database from env var. Adds value beyond schema.
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?
Clearly states 'Execute a read-only SELECT query against MySQL' and explicitly lists permitted statements (SELECT, SHOW, EXPLAIN). Differentiates from sibling mysql_execute for write operations.
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?
Provides explicit guidance: 'Use mysql_execute for write operations.' Includes parameter roles, defaults, and examples. Lacks explicit mention of when to use other siblings like mysql_describe_table, but the distinction is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark destructiveHint=true and readOnlyHint=false. The description adds a clear warning, return format details (affectedRows, insertId, changedRows), and examples. This fully discloses behavioral traits beyond 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?
The description is concise with a clear structure: purpose line, warning, args, returns, and examples. No superfluous text; every element adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must explain return values. It does so with the exact return object shape and concrete examples. Combined with annotations and input schema, the description is fully adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds usage semantics: using ? placeholders, optional bind params, and database fallback to env variable. This provides meaning beyond the schema's property descriptions.
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 explicitly states 'Execute a write SQL statement (INSERT, UPDATE, DELETE, DDL).' The verb 'Execute' and resource 'write SQL statement' are clear, and listing specific SQL types distinguishes it from read-only sibling tools like mysql_query.
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 description warns 'This tool modifies data. Use with caution.' and implicitly separates its write-only purpose from read siblings. However, it lacks explicit guidance on when not to use or direct alternatives, so it's not a full 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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