PostgreSQL Model Context Protocol (PG-MCP) Server

# PostgreSQL Model Context Protocol (PG-MCP) Server A Model Context Protocol (MCP) server for PostgreSQL databases with enhanced capabilities for AI agents. More info on the pg-mcp project here: ### [https://stuzero.github.io/pg-mcp/](https://stuzero.github.io/pg-mcp/) ## Overview PG-MCP is a server implementation of the [Model Context Protocol](https://modelcontextprotocol.io) for PostgreSQL databases. It provides a comprehensive API for AI agents to discover, connect to, query, and understand PostgreSQL databases through MCP's resource-oriented architecture. This implementation builds upon and extends the [reference Postgres MCP implementation](https://github.com/modelcontextprotocol/servers/tree/main/src/postgres) with several key enhancements: 1. **Full Server Implementation**: Built as a complete server with SSE transport for production use 2. **Multi-database Support**: Connect to multiple PostgreSQL databases simultaneously 3. **Rich Catalog Information**: Extracts and exposes table/column descriptions from the database catalog 4. **Extension Context**: Provides detailed YAML-based knowledge about PostgreSQL extensions like PostGIS and pgvector 5. **Query Explanation**: Includes a dedicated tool for analyzing query execution plans 6. **Robust Connection Management**: Proper lifecycle for database connections with secure connection ID handling ## Features ### Connection Management - **Connect Tool**: Register PostgreSQL connection strings and get a secure connection ID - **Disconnect Tool**: Explicitly close database connections when done - **Connection Pooling**: Efficient connection management with pooling ### Query Tools - **pg_query**: Execute read-only SQL queries using a connection ID - **pg_explain**: Analyze query execution plans in JSON format ### Schema Discovery Resources - List schemas with descriptions - List tables with descriptions and row counts - Get column details with data types and descriptions - View table constraints and indexes - Explore database extensions ### Data Access Resources - Sample table data (with pagination) - Get approximate row counts ### Extension Context Built-in contextual information for PostgreSQL extensions like: - **PostGIS**: Spatial data types, functions, and examples - **pgvector**: Vector similarity search functions and best practices Additional extensions can be easily added via YAML config files. ## Installation ### Prerequisites - Python 3.13+ - PostgreSQL database(s) ### Using Docker ```bash # Clone the repository git clone https://github.com/stuzero/pg-mcp-server.git cd pg-mcp-server # Build and run with Docker Compose docker-compose up -d ``` ### Manual Installation ```bash # Clone the repository git clone https://github.com/stuzero/pg-mcp-server.git cd pg-mcp-server # Install dependencies and create a virtual environment ( .venv ) uv sync # Activate the virtual environment source .venv/bin/activate # On Windows: .venv\Scripts\activate # Run the server python -m server.app ``` ## Usage ### Testing the Server The repository includes test scripts to verify server functionality: ```bash # Basic server functionality test python test.py "postgresql://username:password@hostname:port/database" # Claude-powered natural language to SQL conversion python example-clients/claude_cli.py "Show me the top 5 customers by total sales" ``` The `claude_cli.py` script requires environment variables: ``` # .env file DATABASE_URL=postgresql://username:password@hostname:port/database ANTHROPIC_API_KEY=your-anthropic-api-key PG_MCP_URL=http://localhost:8000/sse ``` ### For AI Agents Example prompt for use with agents: ``` Use the PostgreSQL MCP server to analyze the database. Available tools: - connect: Register a database connection string and get a connection ID - disconnect: Close a database connection - pg_query: Execute SQL queries using a connection ID - pg_explain: Get query execution plans You can explore schema resources via: pgmcp://{conn_id}/schemas pgmcp://{conn_id}/schemas/{schema}/tables pgmcp://{conn_id}/schemas/{schema}/tables/{table}/columns A comprehensive database description is available at this resource: pgmcp://{conn_id}/ ``` ## Architecture This server is built on: - **MCP**: The Model Context Protocol foundation - **FastMCP**: Python library for MCP - **asyncpg**: Asynchronous PostgreSQL client - **YAML**: For extension context information ## Security Considerations - The server runs in read-only mode by default (enforced via transaction settings) - Connection details are never exposed in resource URLs, only opaque connection IDs - Database credentials only need to be sent once during the initial connection ## Contributing Contributions are welcome! Areas for expansion: - Additional PostgreSQL extension context files - More schema introspection resources - Query optimization suggestions