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Query SQL databases in natural language with schema-aware SQL generation and self-correction.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "text2sql" MCP server from askskill: Run: claude mcp add 'io-github-cpenniman12-text2sql-mcp' -- npx -y text2sql-mcp
Connect to the database and analyze monthly sales trends for the last 12 months. Aggregate by month, identify the months with the highest growth and steepest decline, and provide the SQL used.
Executable SQL, monthly sales trend results, and a brief analysis of key changes by month.
Inspect the order-related tables and find orders from the last 30 days with unusually high amounts, high refund rates, or duplicate submissions, and explain the filtering logic.
SQL for anomaly detection, a list of flagged orders, and the criteria used for each anomaly type.
Using user signup and activity data, calculate day-1, day-7, and day-30 retention rates for the past 6 months. If the schema is unclear, explore it first and then generate the SQL.
A schema exploration summary, SQL for retention analysis, and retention results broken down by month.
Query any SQL database in natural language with safe auto-generated SQL.
Turn natural language into SQL across databases with document QA and semantic caching.
Query databases in natural language with automatic schema discovery and SQL generation.
Query database schemas in natural language and get fast SQL guidance.
Query MSSQL databases safely in natural language with schema discovery.
Turn data questions into optimized SQL tailored to your database dialect.