Sql queries tool

SQL Query Expert — DBX Studio

This project supports multiple database backends via user connections. Always write dialect-appropriate SQL.

Supported Dialects

Dialect	Provider
PostgreSQL	Default / Railway
Snowflake	Via MCP connector
BigQuery	Via MCP connector
Databricks	Via MCP connector
MySQL	Via connection string
SQLite	Via connection string

Query Patterns

Safe SELECT with limit

Always add LIMIT unless the user explicitly wants all rows:

SELECT * FROM "schema"."table" LIMIT 100;

CTEs for complex queries

WITH ranked AS (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY category ORDER BY created_at DESC) AS rn
  FROM orders
)
SELECT * FROM ranked WHERE rn = 1;

Aggregations

SELECT
  DATE_TRUNC('month', created_at) AS month,
  COUNT(*) AS total,
  SUM(amount) AS revenue
FROM orders
GROUP BY 1
ORDER BY 1 DESC;

Window Functions

SELECT
  user_id,
  amount,
  SUM(amount) OVER (PARTITION BY user_id ORDER BY created_at) AS running_total
FROM transactions;

Tool Usage in DBX Studio AI

The AI has access to these tools — always use them rather than guessing:

Tool	When to Use
read_schema	First call — understand table structure
get_table_data	Preview rows before writing complex queries
execute_query	Run SELECT queries (SELECT/WITH only)
describe_table	Get column details, FK relationships
get_table_stats	Row counts, distributions
generate_chart	Visualize query results

Query Safety Rules

• Only SELECT and WITH (CTEs) are permitted via execute_query
• Always quote identifiers: "schema"."table"."column"
• Add LIMIT automatically unless the user asks for all data
• Validate table/column names exist via read_schema or describe_table first

Response Format

1. Execute tool to get data
2. Answer the user's question directly with the result
3. Show SQL in ```sql blocks only if the user asks "how" or "show me the query"
4. Present numbers clearly: "There are 1,247 orders this month"