sql-formatterFormat and beautify SQL queries.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | SQL query to format | |
| minify | No | Minify instead of format | |
| dialect | No | SQL dialect | standard |
| indentStyle | No | Indent style | 2spaces |
| keywordCase | No | Keyword case | upper |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / properties / dialectAdded value: +{
+ "default": "standard",
+ "description": "SQL dialect",
+ "enum": [
+ "standard",
+ "mysql",
+ "postgresql",
+ "sqlite",
+ "mssql"
+ ],
+ "type": "string"
+}Input schema / properties / indentStyleAdded value: +{
+ "default": "2spaces",
+ "description": "Indent style",
+ "enum": [
+ "2spaces",
+ "4spaces",
+ "tab"
+ ],
+ "type": "string"
+}Input schema / properties / keywordCaseAdded value: +{
+ "default": "upper",
+ "description": "Keyword case",
+ "enum": [
+ "upper",
+ "lower",
+ "preserve"
+ ],
+ "type": "string"
+}Input schema / properties / minifyAdded value: +{
+ "default": false,
+ "description": "Minify instead of format",
+ "type": "boolean"
+}Input schema / properties / sqlAdded value: +{
+ "description": "SQL query to format",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "sql"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only states the basic operation. It does not mention that the tool is non-destructive, whether it validates SQL, what it returns, or error behavior on invalid input. This leaves the agent without critical behavior context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the schema richly documents parameters, the description lacks explicit details about return value, error handling, and dialect behavior (though the schema lists dialects). Despite the tool's simplicity, the absence of any mention of output or failure modes leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all 5 parameters with descriptions, enums, and defaults (100% coverage). The tool description adds no parameter-specific meaning beyond the schema, so it meets the baseline of 3 but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'Format and beautify' with a clear resource 'SQL queries,' which precisely identifies the tool's function. It distinguishes itself from the broader 'code-formatter' sibling by explicitly narrowing scope to SQL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for formatting SQL but provides no explicit guidance on when to use this tool versus alternatives like code-formatter or format-converter. There are no stated exclusions or context signals.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.
Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.
202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.
The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.