PostgreSQL Model Context Protocol (PG-MCP) Server

Name: PostgreSQL Model Context Protocol (PG-MCP) Server
Author: tanster1234

@tanster1234

リポジトリ

PostgreSQL Model Context Protocol (PG-MCP) Server について

概要はまだありません

基本情報

カテゴリ

データベース

ランタイム

python

トランスポート

stdio

公開者

tanster1234

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": {
    "mcp_server_postgres": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

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 PostgreSQL Model Context Protocol (PG-MCP) Server?

It is an MCP server for PostgreSQL databases that provides a comprehensive API for AI agents to discover, connect to, query, and understand PostgreSQL databases through MCP's resource-oriented architecture. It is built for AI agents and developers who need to integrate natural language interfaces with PostgreSQL.

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

Install via Docker or manual setup with Python 3.13+. Run python -m server.app after installing dependencies with uv sync --frozen. Clients connect to the SSE endpoint (default http://localhost:8000/sse) and invoke tools like connect, pg_query, and pg_explain using a secure connection ID.

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

Multi-database support with simultaneous connections.
Rich catalog information from table/column descriptions.
Query execution plan analysis via pg_explain tool.
Built-in extension context for PostGIS and pgvector.
Read-only mode enforced via transaction settings.
Connection pooling and secure opaque connection IDs.

Use cases of PostgreSQL Model Context Protocol (PG-MCP) Server

AI agents exploring database schema and sample data.
Natural language to SQL conversion using Claude CLI.
Automated database introspection for documentation or analysis.
Query performance analysis with execution plan tool.

FAQ from PostgreSQL Model Context Protocol (PG-MCP) Server

What are the runtime requirements?

Python 3.13+ and a PostgreSQL database. The server can be run via Docker or manually.

How do I connect a database?

Use the connect tool with a PostgreSQL connection string to obtain an opaque connection ID for subsequent queries.

Is the server read-only?

Yes, the server runs in read-only mode enforced via transaction settings.

What PostgreSQL extensions are supported?

Built-in context for PostGIS and pgvector is provided, and additional extensions can be added via YAML files.

How is security handled?

Connection details are never exposed in resource URLs; only opaque connection IDs are used. Credentials are sent only once during the initial connection.