Amazon Redshift MCP Server

Category: Database & Messaging MCP Servers
Brand: Amazon Web Services

Overview

The Amazon Redshift MCP Server is an open source Model Context Protocol (MCP) implementation that gives AI agents safe, structured access to Amazon Redshift data warehouses. It connects MCP-compatible tools (such as Amazon Q Developer CLI, Claude Desktop, and Kiro) to Redshift clusters so users can discover, explore, and analyze data and metadata using natural language.

Features

• MCP-based integration

  • Implements the Model Context Protocol to connect AI agents with Amazon Redshift.
  • Acts as a bridge between conversational interfaces and Redshift clusters or workgroups.

• Safe, structured access to Redshift resources

  • Provides controlled access paths to Amazon Redshift resources rather than direct, unconstrained database access.
  • Uses AWS IAM permissions to govern what the MCP server can discover and query.

• Metadata discovery and exploration

  • Allows AI agents to dynamically discover database structures and schemas.
  • Supports exploration of tables and their relationships to give the agent context for query generation.

• Query execution for analytics

  • Translates natural language requests into appropriate Redshift Data API calls and SQL statements.
  • Supports execution and batch execution of SQL via redshift-data:ExecuteStatement and redshift-data:BatchExecuteStatement.
  • Retrieves query status and results with DescribeStatement and GetStatementResult.

• Support for provisioned and serverless Redshift

  • Uses redshift:DescribeClusters for provisioned clusters.
  • Uses redshift-serverless:ListWorkgroups and GetWorkgroup for Redshift Serverless environments.

• Works with multiple MCP-compatible tools

  • Integrates with:
    • Amazon Q Developer CLI
    • Claude Desktop
    • Kiro
    • Other MCP-compatible agents and workflows

• Natural language interface to data

  • Enables conversational querying of Redshift metadata and data.
  • Helps AI agents build context-aware execution plans based on cluster configuration and schemas.

• Open source implementation

  • Available in the AWS Labs GitHub repository.
  • Can be self-hosted and customized as part of existing data and analytics workflows.

• Installation and environment setup (from provided content)

  • Requires uv as a system dependency.
  • Relies on AWS IAM policies with permissions for Redshift, Redshift Serverless, and the Redshift Data API.

Requirements

• System

  • uv installed on the machine running the MCP server (per blog prerequisites).

• AWS

  • An AWS account with Amazon Redshift (provisioned clusters and/or serverless workgroups).
  • IAM permissions including (as shown):
    • redshift:DescribeClusters
    • redshift-serverless:ListWorkgroups
    • redshift-serverless:GetWorkgroup
    • redshift-data:ExecuteStatement
    • redshift-data:BatchExecuteStatement
    • redshift-data:DescribeStatement
    • redshift-data:GetStatementResult

Integrations

• Amazon Redshift (clusters and serverless workgroups)
• Amazon Q Developer CLI
• Claude Desktop
• Kiro
• Any MCP-compatible AI agent or workflow

Pricing

No pricing information is provided in the source content. The component is described as an open source solution; any associated AWS service costs (for Amazon Redshift or related APIs) are not detailed in the provided text.