DB-MCP-Server provides a database connectivity layer for AI assistants through the Model Context Protocol, enabling direct interaction with MySQL and PostgreSQL databases. Built in Go, it supports both local stdio and production SSE transport modes, with configurable database connections through environment variables. The server can be deployed using Docker for easy integration into existing workflows, making it ideal for AI applications that need to query, analyze, or manipulate structured data stored in relational databases without requiring separate database access tools.
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Highlight AIExecute SELECT queries and get results as a tabular dataset. Optional 'mask_pii' boolean redacts PII by content shape.
Run data manipulation statements (INSERT, UPDATE, DELETE). Optional 'dry_run' boolean classifies the statement offline and executes nothing.
Begin, commit, and rollback transactions. Also carries the undo actions: 'list_snapshots' and 'rollback_snapshot' (with 'snapshot_id').
Get information about tables, columns, indexes, and foreign keys.
Generate SQL or code from database schema.
Analyze query performance via various actions like 'stats', 'slow_queries', 'suggest', etc.
Show the execution plan for a SQL statement without running it.
Inspect one table's columns, indexes, and row estimate via engine catalog queries.
Report connectivity, ping latency, connection-pool state, and engine stats.
Execute optimized time-series queries with time bucketing, filtering, and window functions.
Analyze time-series patterns for one table/column.
List hypertables with their time column and dimension count.
Show compression configuration for hypertables.
Show configured retention policies.
List continuous aggregates with bucket interval and refresh policy.
Inspect one continuous aggregate in detail.
