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j4c0bs/mcp-server-sql-analyzer

MCP server for SQL static analysis.

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许可证
MIT

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2026 年 2 月 1 日 新增 0 个星标; 2026 年 2 月 14 日 新增 0 个星标; 2026 年 3 月 16 日 新增 2 个星标

窗口内最高的一天是 2026 年 3 月 16 日,新增 2 个星标。

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README
The document stored for this repository, with its Chinese translation when one has been produced

mcp-server-sql-analyzer

A Model Context Protocol (MCP) server that provides SQL analysis, linting, and dialect conversion capabilities using SQLGlot.

Overview

The SQL Analyzer MCP server provides tools for analyzing and working with SQL queries. It helps with:

  • SQL syntax validation and linting
  • Converting queries between different SQL dialects (e.g., MySQL to PostgreSQL)
  • Extracting and analyzing table references and dependencies
  • Identifying column usage and relationships
  • Discovering supported SQL dialects

How Claude Uses This Server

As an AI assistant, this server enhances my ability to help users work with SQL efficiently by:

  1. Query Validation: I can instantly validate SQL syntax before suggesting it to users, ensuring I provide correct and dialect-appropriate queries.

  2. Dialect Conversion: When users need to migrate queries between different database systems, I can accurately convert the syntax while preserving the query's logic.

  3. Code Analysis: The table and column reference analysis helps me understand complex queries, making it easier to explain query structure and suggest optimizations.

  4. Compatibility Checking: By knowing the supported dialects and their specific features, I can guide users toward database-specific best practices.

This toolset allows me to provide more accurate and helpful SQL-related assistance while reducing the risk of syntax errors or dialect-specific issues.

Tips

Update your personal preferences in Claude Desktop settings to request that generated SQL is first validated using the lint_sql tool.

Tools

  1. lint_sql

    • Validates SQL query syntax and returns any errors
    • Input:
      • sql (string): SQL query to analyze
      • dialect (string, optional): SQL dialect (e.g., 'mysql', 'postgres')
    • Returns: ParseResult containing:
      • is_valid (boolean): Whether the SQL is valid
      • message (string): Error message or "No syntax errors"
      • position (object, optional): Line and column of error if present
  2. transpile_sql

    • Converts SQL between different dialects
    • Inputs:
      • sql (string): SQL statement to transpile
      • read_dialect (string): Source SQL dialect
      • write_dialect (string): Target SQL dialect
    • Returns: TranspileResult containing:
      • is_valid (boolean): Whether transpilation succeeded
      • message (string): Error message or success confirmation
      • sql (string): Transpiled SQL if successful
  3. get_all_table_references

    • Extracts table and CTE references from SQL
    • Inputs:
      • sql (string): SQL statement to analyze
      • dialect (string, optional): SQL dialect
    • Returns: TableReferencesResult containing:
      • is_valid (boolean): Whether analysis succeeded
      • message (string): Status message
      • tables (array): List of table references with type, catalog, database, table name, alias, and fully qualified name
  4. get_all_column_references

    • Extracts column references with table context
    • Inputs:
      • sql (string): SQL statement to analyze
      • dialect (string, optional): SQL dialect
    • Returns: ColumnReferencesResult containing:
      • is_valid (boolean): Whether analysis succeeded
      • message (string): Status message
      • columns (array): List of column references with column name, table name, and fully qualified name

Resources

SQL Dialect Discovery

dialects://all

Returns a list of all supported SQL dialects for use in all tools.

Configuration

Using uvx (recommended)

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
      "sql-analyzer": {
          "command": "uvx",
          "args": [
              "--from",
              "git+https://github.com/j4c0bs/mcp-server-sql-analyzer.git",
              "mcp-server-sql-analyzer"
          ]
      }
  }
}

Using uv

After cloning this repo, add this to your claude_desktop_config.json:

{
  "mcpServers": {
      "sql-analyzer": {
          "command": "uv",
          "args": [
              "--directory",
              "/path/to/mcp-server-sql-analyzer",
              "run",
              "mcp-server-sql-analyzer"
          ]
      }
  }
}

Development

To run the server in development mode:

# Clone the repository
git clone git@github.com:j4c0bs/mcp-server-sql-analyzer.git

# Run the server
npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-server-sql-analyzer run mcp-server-sql-analyzer

To run unit tests:

uv run pytest .

License

MIT

页面上的每个数字都来自记录下来的 stargazer 到达时间,没有评分公式,也没有 AI 判定。 任何结论都可以用 /api/v1/repos/{id}/stats 里的原始增量自己重算。