AI-Powered SQL Query Generation from Database Schema

This advanced n8n workflow automates the process of generating SQL queries based solely on a database schema, leveraging AI to facilitate data retrieval without exposing sensitive data. It begins by connecting to a MySQL database and fetching a list of all tables. For each table, it extracts the schema information and converts it into a JSON format, which is stored locally. During user interactions, such as chat messages via a webhook trigger, the workflow loads the schema data from the local file, making the process faster and resource-efficient.

A LangChain AI agent — configured to understand the database structure — assists in generating appropriate SQL queries based on user prompts. The agent only creates queries when needed, avoiding unnecessary database calls. When an SQL query is identified in the AI’s response, the workflow executes it against the database, retrieves the results, and formats them into a human-readable markdown block. The final output combines the AI’s explanation with the raw SQL results, providing a comprehensive message back to the user.

This workflow is especially useful in scenarios where users need to explore or analyze database content quickly and securely, without direct database access or risking exposure of actual data. It enhances data interaction via AI, streamlining data analysis, reporting, or support tasks within a WordPress or other ecosystem.