Summary
Redshift, with the schema already on the table.
The assistant browses schemas and DDL as resources before writing a query, then reads the execution plan instead of discovering the cost by running it.
What it is
A Python server for Amazon Redshift. Three tools do the work — run SQL, read a plan, analyze a table — while schemas, table lists, DDL and table statistics are exposed as MCP resources the client can browse before it writes anything.
What you get
- execute_sql runs a query against the cluster
- get_execution_plan returns the plan for a query before you commit to running it
- analyze_table collects statistics on a table
- Resources cover the reading: rs:///schemas lists schemas, rs:///{schema}/tables lists tables, and each table's DDL and statistics have their own rs:/// address
Requirements
Python 3.13 or higher, uv, and a reachable Redshift cluster. Connection details come from environment variables: RS_HOST, RS_PORT, RS_USER, RS_PASSWORD, RS_DATABASE and an optional RS_SCHEMA.
Setup effort
Build from source — clone the repository and build it, then point your client at the binary