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Redshift MCP Server

@Moonlight-CL

Repository

Basic information

Category

Other

License

Apache-2.0

Transports

stdio

Author

Moonlight-CL

About Redshift MCP Server

No overview available yet

Redshift MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "redshift-mcp-server-moonlight-cl": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Redshift MCP Server tools

3

Executes a SQL query on the Redshift cluster

Analyzes a table to collect statistics information

Gets the execution plan with runtime statistics for a SQL query

Overview

What is Redshift MCP Server?

A Python-based Model Context Protocol (MCP) server that enables AI assistants to interact with Amazon Redshift databases. It provides tools and resources for listing schemas and tables, retrieving table DDL, getting table statistics, executing SQL queries, analyzing tables, and obtaining execution plans.

How to use Redshift MCP Server?

Install Python 3.13 or higher and have a running Redshift cluster with credentials. Clone the repository, install dependencies with uv sync, and set environment variables (RS_HOST, RS_PORT, RS_USER, RS_PASSWORD, RS_DATABASE, and optionally RS_SCHEMA). Start the server with uv run --with mcp python-dotenv redshift-connector mcp and mcp run src/redshift_mcp_server/server.py. Integrate with an MCP-compatible AI assistant by adding the provided JSON configuration to your MCP settings file.

Key features of Redshift MCP Server

  • Lists all schemas and tables in the database
  • Retrieves DDL scripts for any table
  • Provides table statistics (row count, size, etc.)
  • Executes arbitrary SQL queries on the cluster
  • Analyzes tables to collect fresh statistics
  • Returns execution plans with runtime statistics

Use cases of Redshift MCP Server

  • Exploring database schemas and table structures via an AI assistant
  • Inspecting table definitions and DDL for migration or documentation
  • Running ad‑hoc SQL queries without connecting directly to Redshift
  • Collecting table statistics to optimize query performance
  • Debugging slow queries by reviewing execution plans

Frequently asked questions

1

What are the runtime requirements?

Python 3.13 or higher is required. The server also needs network access to an Amazon Redshift cluster and valid database credentials.

2

How do I connect to my Redshift cluster?

Set the environment variables `RS_HOST`, `RS_PORT`, `RS_USER`, `RS_PASSWORD`, `RS_DATABASE`, and optionally `RS_SCHEMA`. These can be set directly or in a `.env` file.

3

What dependencies does the server use?

It depends on the MCP CLI package (`mcp[cli]>=1.5.0`), `python-dotenv>=1.1.0` for environment variable loading, and `redshift-connector>=2.1.5` for Redshift connectivity.

4

What data does the server access?

All data lives in the connected Amazon Redshift database. The server does not store any data locally; it only queries and returns results from the cluster.

5

What authentication method does it use?

Authentication is handled via username and password passed as environment variables (`RS_USER` and `RS_PASSWORD`). No other authentication mechanisms are documented.

Comments

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