What are the runtime requirements?
Python 3.13+ and a PostgreSQL database. The server can be run via Docker or manually.
@tanster1234
基本情報
概要はまだありません
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"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
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。
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.
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.
pg_explain tool.Python 3.13+ and a PostgreSQL database. The server can be run via Docker or manually.
Use the `connect` tool with a PostgreSQL connection string to obtain an opaque connection ID for subsequent queries.
Yes, the server runs in read-only mode enforced via transaction settings.
Built-in context for PostGIS and pgvector is provided, and additional extensions can be added via YAML files.
Connection details are never exposed in resource URLs; only opaque connection IDs are used. Credentials are sent only once during the initial connection.
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