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Run SQL in an ephemeral real database with results, errors, plans, and diffs.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "sqlai.dev SQL Verifier" MCP server from askskill: Run: claude mcp add --transport http 'io-github-jadesparrow-sqlai-dev-sql-verifier' 'https://mcp.sqlai.dev/mcp'
Execute this SQL in an ephemeral database and return rows, typed errors, and suggested fixes: SELECT id, email FROM users WHERE created_at > '2024-01-01';
Returns query rows; if the SQL is invalid, it provides a typed error and fix suggestions.
Run this SQL in a real ephemeral database and output the execution plan so I can check for inefficient scans: SELECT * FROM orders WHERE customer_id = 42 ORDER BY created_at DESC;
Provides the SQL execution plan to help assess how the query runs and spot possible performance issues.
Compare the results or diffs between these two SQL versions and point out possible impact: Old: SELECT name FROM products; New: SELECT id, name FROM products WHERE active = true;
Outputs diffs between the two SQL versions so you can review changes in fields, filters, or results.
Developers can run queries or migration-related SQL in an ephemeral real database before shipping, verify the results, and catch typed errors with suggested fixes.
Data or engineering teams can inspect SQL execution plans to understand how a query runs and to investigate possible performance issues.
When a SQL statement changes, the diff output can help compare before-and-after behavior for code review or result verification.
It executes SQL in a real but ephemeral database environment and returns rows, typed errors with suggestions, execution plans, and diffs.
Based on the description, no. It emphasizes executing SQL in a real ephemeral database, so it can return actual results and execution plans, not just validation.
The provided material does not include installation steps, runtime details, or key requirements. See the source repository for prerequisites.
Query, analyze, and manage SQL Server databases using natural language.
Query SQL databases in natural language with schema-aware SQL generation and self-correction.
Lets AI safely explore SQL schemas and run read-only database queries.
Safely run database queries for AI workflows with built-in security controls.
Query databases in natural language with automatic schema discovery and SQL generation.
Connect AI to SQL Server for querying, schema exploration, reports, and charts.