MCPg : Production Grade Postgresql Mcp Server

Name: MCPg : Production Grade Postgresql Mcp Server
Author: devopam

@devopam

リポジトリ

MCPg : Production Grade Postgresql Mcp Server について

A safe-by-default PostgreSQL Model Context Protocol server for AI agents.

#mcp #server #postgresql

基本情報

カテゴリ

データベース

トランスポート

stdio

公開者

devopam

投稿者

Devopam Mittra

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcpg": {
      "command": "uvx",
      "args": [
        "mcpg"
      ],
      "env": {
        "MCPG_DATABASE_URL": "postgresql://user:pass@localhost:5432/mydb"
      }
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCPg?

MCPg is a production-grade MCP server for PostgreSQL that provides AI agents with over 100 tools for schema introspection, natural-language-to-SQL, query optimization, index tuning, performance analysis, multi-tenancy operations, and DBA tasks, prioritizing safety.

How to use MCPg?

Install via pip install mcpg or Docker. Configure connection settings and choose a transport: stdio for Claude Desktop, or HTTP/SSE/Streamable HTTP. Connect any MCP client to start using the tools.

Key features of MCPg

Safety-first design: read-only by default, AST validation, strict sanitization
Broad PostgreSQL support: pgvector, TimescaleDB, PostGIS, Apache AGE
Production ready: connection pooling, SET ROLE multi-tenancy, read-replica routing
Prometheus metrics and structured audit logging with redaction
Multiple transports: stdio, HTTP, SSE, Streamable HTTP
Easy install: pip or Docker with OIDC + static auth and rate limiting

Use cases of MCPg

AI-assisted schema exploration and database introspection
Natural language to SQL query generation and optimization
Automated index tuning and performance analysis
Multi-tenant database operations with role isolation
Production DBA tasks with safety guards

FAQ from MCPg

What tools does MCPg provide?

Over 100 tools covering schema introspection, natural-language-to-SQL, query optimization, index tuning, performance analysis, multi-tenancy operations, and DBA tasks.

How does MCPg ensure safety?

It is read-only by default, performs AST validation on all SQL, strictly sanitizes identifiers, and requires opt-in gates for DDL, shell commands, and LISTEN operations.

What transports are supported?

MCPg supports stdio (for Claude Desktop), HTTP, Server-Sent Events (SSE), and Streamable HTTP.

Is MCPg production ready?

Yes, it includes connection pooling, SET ROLE multi-tenancy, read-replica routing, Prometheus metrics, structured audit logging, OIDC + static authentication, and rate limiting.

What are the runtime requirements?

Python (psycopg3 driver), a PostgreSQL database, and optional extensions like pg_stat_statements for performance features.

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