Provides SQL query formatting for MariaDB dialect, with configurable tab width and uppercase keywords.
Provides SQL query formatting for MySQL dialect, with configurable tab width and uppercase keywords.
Provides SQL query formatting for PostgreSQL dialect, with configurable tab width and uppercase keywords.
Provides SQL query formatting for Snowflake dialect, with configurable tab width and uppercase keywords.
Provides SQL query formatting for SQLite dialect, with configurable tab width and uppercase keywords.
Provides SQL query formatting for Trino dialect, with configurable tab width and uppercase keywords.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@sql-mcp format this SQL: select id, name from users"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server: format SQL queries. Backed by sql-formatter, supports 14
dialects.
format{ "sql": "select id, name from users where age > 21 order by id", "dialect": "postgresql" }→
SELECT
id,
name
FROM
users
WHERE
age > 21
ORDER BY
idField | Default | Notes |
|
|
|
| 2 | 0-8 |
| true | Uppercase keywords (SELECT, FROM, …) |
Related MCP server: GoSQLX
{ "mcpServers": { "sql": { "command": "npx", "args": ["-y", "@mukundakatta/sql-mcp"] } } }MIT.
Format a SQL query. Supports 14 dialects (Postgres, MySQL, SQLite, BigQuery, Snowflake, MSSQL, etc.). Default uppercases keywords.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | ||
| dialect | No | sql | |
| tab_width | No | ||
| uppercase | No | Uppercase keywords (SELECT, FROM, etc.). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context by mentioning the default keyword uppercasing and the number of supported dialects. However, it does not disclose error handling, authentication requirements, or behavior with invalid input. With no annotations, the description carries the full burden, and while it adds some value, it lacks depth on potential side effects.
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 concise (two sentences) and front-loaded with the action. Every sentence provides necessary information: the primary function, the range of dialects, and a key default. There is no unnecessary text.
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?
The tool is simple with no output schema and no siblings. The description covers the core functionality, supported dialects, and default behavior. It lacks details on return format and error handling, but for a formatting tool these are minor gaps. Overall, it provides sufficient context for an AI agent to understand and invoke the tool correctly.
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?
Schema description coverage is low (25% for only the 'uppercase' parameter). The description adds context for the 'uppercase' parameter by explaining the default behavior, and it clarifies the 'dialect' parameter by enumerating 14 dialects. However, it does not explain the 'sql' or 'tab_width' parameters, so the description only partially compensates for the low schema coverage.
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 clearly states the tool formats SQL queries, specifies the supported dialects, and mentions the default behavior of uppercasing keywords. It uses a specific verb ('Format') and resource ('SQL query'), making the purpose unambiguous.
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 when to use the tool (when formatting SQL) and lists supported dialects, but does not explicitly state when not to use it or provide exclusion criteria. Since no sibling tools exist, the guidance is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0formatOnly one tool exists, so there is no ambiguity. The tool's purpose is clearly defined.
With a single tool, naming consistency is trivially maintained. The name 'format' is a clear verb indicating its action.
A single tool for a SQL server is far too sparse. Users would expect multiple tools for querying, explaining, or managing databases.
The server only offers formatting, missing essential SQL operations like executing queries or analyzing schema, making it severely incomplete.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Format/lint JS, Python, HubL for automation platforms. Tools: format_code, format_json, ask_codefmt
Generate, fix, explain and run read-only SQL on PostgreSQL, MySQL and SQL Server
Kotlin compile-time SQL library. Docs, code validation, and SQLite execution tools.
Executes SQL in a real ephemeral database: rows, typed errors with suggestions, plans, diffs.
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/MukundaKatta/sql-mcp'
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