PostgreSQL Model Context Protocol (PG-MCP) Server

Name: PostgreSQL Model Context Protocol (PG-MCP) Server
Author: stuzero

@stuzero

代码仓库

关于 PostgreSQL Model Context Protocol (PG-MCP) Server

暂无概览

基本信息

分类

数据库

许可证

MIT

运行时

python

传输方式

stdio

发布者

stuzero

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "pg-mcp-server": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is PostgreSQL Model Context Protocol (PG-MCP) Server?

PG-MCP is a server implementation of the Model Context Protocol (MCP) 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. The server includes multi-database support, rich catalog information, built-in extension context (e.g., PostGIS, pgvector), and query explanation tools.

How to use PostgreSQL Model Context Protocol (PG-MCP) Server?

Install via Docker (docker-compose up -d) or manually (uv sync, then python -m server.app). Use the provided test scripts (test.py and example-clients/claude_cli.py) to verify functionality. For AI agents, use the server’s tools (connect, disconnect, pg_query, pg_explain) and explore schema resources via pgmcp://{conn_id}/ URIs.

Key features of PostgreSQL Model Context Protocol (PG-MCP) Server

Connect tool to register PostgreSQL connection strings and get a secure connection ID
Read-only SQL execution (pg_query) with connection ID
pg_explain tool to analyze query execution plans in JSON
Schema discovery: list schemas, tables, columns, constraints, indexes, extensions
Sample table data with pagination and approximate row counts
Built-in YAML-based context for extensions like PostGIS and pgvector