PostgreSQL MCP Server

PostgreSQL MCP servers enable AI models to interact with PostgreSQL databases, providing capabilities for structured data operations, SQL queries, transaction management, and advanced data indexing.

{
  "mcpServers": {
    "postgres": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-postgres-server"
      ],
      "env": {
        "PG_HOST": "your_host",
        "PG_PORT": "5432",
        "PG_USER": "your_user",
        "PG_PASSWORD": "your_password",
        "PG_DATABASE": "your_database"
      }
    }
  }
}

Overview

The MCP Postgre Server bridges AI and databases by letting language models (LLMs) work directly with PostgreSQL. It's part of the Model Context Protocol (MCP) system, providing a safe and standard way to connect AI with data. 1

Anton Orlov

Key features include:

  • View and understand database structures
  • Convert natural language to SQL queries
  • Handle query results effectively
  • Format data for easy reading

Tools

Sources

Footnotes

  1. https://github.com/antonorlov/mcp-postgres-server ↩

Related Articles

Screen Shot One MCP Servers

Screen Shot One MCP Servers

Deepseek - Open Source AI Code Model

An overview of Deepseek, a powerful open-source AI code model. Learn about its capabilities, use cases, and how to leverage it for code generation, completion, and analysis in your development workflow.

Retrieval Augmented Thinking MCP Servers

Learn how to implement Retrieval Augmented Generation (RAG) in MCP servers to enhance AI responses with relevant information from external knowledge bases.