DBX

Configure an AI provider to generate SQL, explain queries, suggest optimizations, and help fix errors in DBX.

The AI assistant helps with SQL work. It uses metadata from the active connection to understand tables and columns, then helps generate SQL, explain queries, suggest optimizations, or diagnose errors.

AI-generated SQL is not executed automatically. Review table names, columns, filters, and affected rows before running it, especially on production connections.

Configuration

Open Settings

Open DBX settings and find the AI configuration section.

Choose a Provider

Select Anthropic, OpenAI, or a custom endpoint compatible with the OpenAI API.

Enter Credentials

Enter your API key. For custom endpoints, also enter the endpoint URL and model name.

Save and Test

Save the configuration, return to the editor, and try generating a simple query from natural language.

When no API key is configured, AI features should prompt the user to complete setup instead of failing silently.

Ask Mode And Agent Mode

Mode	Behavior	Execution
Ask	Generates SQL, explanations, fixes, optimizations, dialect conversions, or sample data	Does not imply anything has run
Agent	Prioritizes one executable SQL statement when the user clearly asks DBX to query data	DBX evaluates the generated SQL before attempting execution

Schema Context

AI prompts can include the current database type, connection name, database, current SQL, recent error, result preview, and schema context. Schema context contains tables, columns, indexes, and foreign keys.

When a schema is large, DBX truncates context. Use @table or @schema.table mentions in your prompt to prioritize the tables you want AI to reason about.

SQL Safety Policy

SQL Category	DBX Behavior
Read-only statements such as `SELECT`, `WITH`, `SHOW`, `DESCRIBE`, `DESC`, `EXPLAIN`	Can be auto-executed in Agent mode when the user clearly asks to query
Scoped low-risk writes such as `INSERT` or keyed `UPDATE`	Auto-execute only in clearly non-production environments; otherwise confirm
Multiple statements, `DELETE`, `MERGE`, `REPLACE`, `CREATE`, or unknown SQL	Confirm before execution
Dangerous statements such as `DROP`, `TRUNCATE`, `ALTER`, `RENAME`, or broad `UPDATE`	Blocked by the AI execution policy

Production-like connection names, hosts, or database names make DBX more conservative. Generated SQL is still text from an AI model; review it like code before trusting it.

Common Uses

Generate SQL

Describe the result you want, and the assistant generates SQL using metadata from the current connection:

Show the top 10 customers by order amount in the last 30 days

Example output:

SELECT c.name, SUM(o.amount) AS total_amount
FROM customers c
JOIN orders o ON c.id = o.customer_id
WHERE o.created_at >= NOW() - INTERVAL 30 DAY
GROUP BY c.id, c.name
ORDER BY total_amount DESC
LIMIT 10;

Before running generated SQL, check:

Whether the tables and columns are correct
Whether the time range matches your intent
Whether aggregation and ordering are correct
Whether the result should be limited

Explain SQL

Select SQL and ask the assistant to explain its structure:

What each subquery does
How JOIN conditions connect tables
What the WHERE clause filters
How aggregation, grouping, and sorting work

This is useful for reading legacy queries, reports, or complex views.

Optimize SQL

The assistant can suggest optimization directions, such as:

Possible full table scans
Missing indexes
Subqueries that may be rewritten as JOIN
Sorting, deduplication, or aggregation that could be reduced

AI optimization suggestions are advisory. Confirm performance with the database execution plan, data volume, and index design.

Fix Errors

When SQL fails, send the error and query to the assistant for diagnosis. Common fixes include:

Syntax errors
Misspelled table or column names
Missing GROUP BY columns
Type mismatches
Dialect differences between database engines

Supported Providers

Use this for Claude models. Enter your API key, then choose or type the model you want to use.

Use this for OpenAI models. Enter your API key, then choose or type the model you want to use.

Use this for services compatible with the OpenAI Chat Completions API, such as local model servers, enterprise gateways, or third-party model platforms.

Configure:

Endpoint URL
API key
Model

Privacy and Security

AI requests may include your prompt, SQL, error messages, and the schema context needed to answer. Before using an external provider, confirm:

Whether sending this information is allowed
Whether it includes sensitive field names, business logic, or sample data
Whether your team has compliance rules for third-party model calls

If you want AI agents to query databases through tools, continue with MCP Integration.

AI Assistant