What is Sample Amazon Redshift Mcp Server

The sample-amazon-redshift-MCP-server is a Model Context Protocol (MCP) server designed for Amazon Redshift, enabling AI assistants to interact seamlessly with Redshift databases.

Use cases

Use cases include automated reporting, data analysis, and enhancing AI assistants with capabilities to query and analyze data stored in Amazon Redshift.

How to use

To use the sample-amazon-redshift-MCP-server, install it by cloning the repository and installing dependencies. Configure the necessary environment variables for your Redshift cluster, and integrate it with your AI assistant by adding the required MCP settings.

Key features

Key features include the ability to list schemas and tables, retrieve table DDL scripts, get table statistics, execute SQL queries, analyze tables for statistics, and obtain execution plans for SQL queries.

Where to use

This MCP server is suitable for data analytics, business intelligence, and any application that requires interaction with Amazon Redshift databases.

Redshift MCP Server

A Model Context Protocol (MCP) server for Amazon Redshift that enables AI assistants to interact with Redshift databases.

Introduction

Redshift MCP Server is a Python-based implementation of the Model Context Protocol that provides tools and resources for interacting with Amazon Redshift databases. It allows AI assistants to:

• List schemas and tables in a Redshift database
• Retrieve table DDL (Data Definition Language) scripts
• Get table statistics
• Execute SQL queries
• Analyze tables to collect statistics information
• Get execution plans for SQL queries

Installation

Prerequisites

• Python 3.13 or higher
• Amazon Redshift cluster
• Redshift credentials (host, port, username, password, database)

Install from source

# Clone the repository
git clone https://github.com/aws-samples/sample-amazon-redshift-MCP-server.git
cd sample-amazon-redshift-MCP-server

# Install dependencies
uv sync

Configuration

The server requires the following environment variables to connect to your Redshift cluster:

RS_HOST=your-redshift-cluster.region.redshift.amazonaws.com
RS_PORT=5439
RS_USER=your_username
RS_PASSWORD=your_password
RS_DATABASE=your_database
RS_SCHEMA=your_schema  # Optional, defaults to "public"

Usage

Integrating with AI assistants

To use this server with an AI assistant that supports MCP, add the following configuration to your MCP settings:

{
  "mcpServers": {
    "redshift": {
      "command": "uv",
      "args": [
        "--directory",
        "src/redshift_mcp_server",
        "run",
        "server.py"
      ],
      "env": {
        "RS_HOST": "your-redshift-cluster.region.redshift.amazonaws.com",
        "RS_PORT": "5439",
        "RS_USER": "your_username",
        "RS_PASSWORD": "your_password",
        "RS_DATABASE": "your_database",
        "RS_SCHEMA": "your_schema"
      }
    }
  }
}

Features

Resources

The server provides the following resources:

• rs:///schemas - Lists all schemas in the database
• rs:///{schema}/tables - Lists all tables in a specific schema
• rs:///{schema}/{table}/ddl - Gets the DDL script for a specific table
• rs:///{schema}/{table}/statistic - Gets statistics for a specific table

Tools

The server provides the following tools:

• execute_sql - Executes a SQL query on the Redshift cluster
• analyze_table - Analyzes a table to collect statistics information
• get_execution_plan - Gets the execution plan with runtime statistics for a SQL query

Examples

Listing schemas

access_mcp_resource("redshift-mcp-server", "rs:///schemas")

Listing tables in a schema

access_mcp_resource("redshift-mcp-server", "rs:///public/tables")

Getting table DDL

access_mcp_resource("redshift-mcp-server", "rs:///public/users/ddl")

Executing SQL

use_mcp_tool("redshift-mcp-server", "execute_sql", {"sql": "SELECT * FROM public.users LIMIT 10"})

Analyzing a table

use_mcp_tool("redshift-mcp-server", "analyze_table", {"schema": "public", "table": "users"})

Getting execution plan

use_mcp_tool("redshift-mcp-server", "get_execution_plan", {"sql": "SELECT * FROM public.users WHERE user_id = 123"})

Development

Project structure

redshift-mcp-server/
├── src/
│   └── redshift_mcp_server/
│       ├── __init__.py
│       └── server.py
├── pyproject.toml
└── README.md

Dependencies

• mcp[cli]>=1.5.0 - Model Context Protocol SDK
• python-dotenv>=1.1.0 - For loading environment variables from .env files
• redshift-connector>=2.1.5 - Python connector for Amazon Redshift