superset-mcp

format_sql

Format and structure SQL queries for improved readability and debugging within Apache Superset environments.

Instructions

Format/pretty-print a SQL query.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sql": "<sql>"
    },
    "name": "format_sql"
  }
}

Input Schema

Name	Required	Description	Default
`sql`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 14, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action but doesn't explain what formatting entails (e.g., indentation, capitalization rules), whether it validates SQL syntax, handles errors, or has performance implications. This leaves significant gaps for a tool that modifies input.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.

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

Completeness3/5

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

Given the tool's moderate complexity (formatting SQL), no annotations, and an output schema that likely handles return values, the description is minimally adequate. It covers the core action but lacks details on behavior, parameters, and usage context, making it incomplete for full agent guidance.

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?

The input schema has 0% description coverage, with one parameter 'sql' undocumented. The description implies 'sql' is a SQL query to format, adding basic meaning beyond the schema. However, it doesn't specify format requirements (e.g., plain text, supported dialects), so it only partially compensates for the schema gap.

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?

The description clearly states the tool's purpose with a specific verb ('format/pretty-print') and resource ('SQL query'), making it immediately understandable. However, it doesn't distinguish this formatting tool from sibling tools like execute_sql or save_query, which prevents a perfect score.

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. With siblings like execute_sql and save_query that might also handle SQL queries, there's no indication of when formatting is preferred over execution or saving, leaving usage context unclear.

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