redshift-mcp-server

# 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](https://github.com/modelcontextprotocol/mcp) 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 ```bash # Clone the repository git clone https://github.com/Moonlight-CL/redshift-mcp-server.git cd 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" ``` You can set these environment variables directly or use a `.env` file. ## Usage ### Starting the server ```bash # Start the server uv run --with mcp python-dotenv redshift-connector mcp mcp run src/redshift_mcp_server/server.py ``` ### Integrating with AI assistants To use this server with an AI assistant that supports MCP, add the following configuration to your MCP settings: ```json { "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