This Database SQL Query Agent convert natural language into sql query to get results
Turn your PostgreSQL database into a conversational AI agent! Ask questions in plain English and get instant data results without writing SQL.
✨ What It Does
- Natural Language Queries : "Show laptops under $500 in stock" → Automatic SQL generation
- Smart Column Mapping : Understands your terms and maps them to actual database columns
- Conversational Memory : Maintains context across multiple questions
- Universal Compatibility : Works with any PostgreSQL table structure
🎯 Perfect For
- Business analysts querying data without SQL knowledge
- Customer support finding information quickly
- Product managers analyzing inventory/sales data
- Anyone who needs database insights fast
🚀 Quick Setup
Step 1: Prerequisites
- n8n instance (cloud/self-hosted)
- PostgreSQL database with read access
- OpenAI API key/You can use other LLM as well
Step 2: Import & Configure
- Import this workflow template into n8n
- Add Credentials :
- OpenAI API: Add your API key
- PostgreSQL: Configure database connection
- Set Table Name : Edit "Set Table Name" node → Replace
"table_name" with your actual table
- Test Connection : Ensure your database user has SELECT permissions
Step 3: Deploy & Use
- Start the workflow
- Open the chat interface
- Ask questions like:
- "Show all active users"
- "Find orders from last month over $100"
- "List products with low inventory"
🔧 Configuration Details
Required Settings
- Table Name : Update in "Set Table Name" node
- Database Schema : Default is 'public' (modify SQL if different)
- Result Limit : Default 50 rows (adjustable in system prompt)
Optional Customizations
- Multi-table Support : Modify system prompt and add table selection logic
- Custom Filters : Add business rules to restrict data access
- Output Format : Customize response formatting in the agent prompt
💡 Example Queries
E-commerce
"Show me all electronics under $200 that are in stock"
HR Database
"List employees hired in 2024 with salary over 70k"
Customer Data
"Find VIP customers from California with recent orders"
🛡️ Security Features
- Read-only Operations : Only SELECT queries allowed
- SQL Injection Prevention : Parameterized queries and validation
- Result Limits : Prevents overwhelming queries
- Safe Schema Discovery : Uses information_schema tables
🔍 How It Works
- Schema Discovery : Agent fetches table structure and column info
- Query Planning : Maps natural language to database columns
- SQL Generation : Creates safe, optimized queries
- Result Formatting : Returns clean, user-friendly data
⚡ Quick Troubleshooting
- No Results : Check table name and ensure data exists
- Permission Error : Verify database user has SELECT access
- Connection Failed : Confirm PostgreSQL credentials and network access
- Unexpected Results : Try more specific queries with exact column names
🎨 Use Cases
- Inventory Management : "Show low-stock items by category"
- Sales Analysis : "Top 10 products by revenue this quarter"
- Customer Support : "Find customer orders with status 'pending'"
- Data Exploration : "What are the unique product categories?"
🔧 Advanced Tips
- Performance : Add database indexes on frequently queried columns
- Customization : Modify the system prompt for domain-specific terminology
- Scaling : Use read replicas for high-query volumes
- Integration : Connect to Slack/Teams for team-wide data access
Tags : AI, PostgreSQL, Natural Language, SQL, Business Intelligence, LangChain, Database Query
Difficulty : Beginner to Intermediate
Setup Time : 10-15 minutes
