"Creating a Postgres MCP server in Python" matching MCP servers:

A Postgres MCP server with index tuning, explain plans, health checks, and safe SQL execution.

A Postgres MCP server with index tuning, explain plans, health checks, and safe SQL execution for AI agents.

Postgres Pro is an open source Model Context Protocol (MCP) server built to support you and your AI agents throughout the entire development process—from initial coding, through testing and deployment, and to production tuning and maintenance.

A Postgres MCP server with index tuning, explain plans, health checks, and safe sql execution.

Enables AI coding assistants to browse Unreal Python API documentation, search classes and functions, and execute Python code in Unreal Editor.

Python Docs MCP Server gives AI coding agents local access to the official Python standard library docs. It can look up docs by Python version, return specific sections, and keep answers compact for clients like Claude Desktop, Cursor, and Codex. It runs without API keys or a hosted service.

A Python MCP server that generates complete Vue 3 CRUD structures with Composition API, including components, services, stores, and routes.

A Python MCP server for Metabase that enables AI assistants to query databases, manage dashboards, and interact with your Metabase instance.

An MCP server that exposes Python debugging tools backed by debugpy, providing a focused debugging surface for local scripts.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A self-hostable PostgreSQL MCP server for exploring database schemas and running guarded read/write queries with selectable access modes (readonly, readwrite, admin), plus a dry-run confirm workflow for safety.

Governed PostgreSQL DBA operations — slow-query, bloat, and blocking-lock RCA, index management, vacuum/analyze, and replication lag, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

Enables AI agents to analyze, optimize, and safely interact with PostgreSQL databases, including health checks, index recommendations, query planning, and SQL execution with read-only and production protection modes.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

A Python-based MCP server that enables users to interact with the esa.io API for documentation management. It provides tools for retrieving user information and performing full CRUD operations on articles.

Exposes PostgreSQL query execution, EXPLAIN, and schema inspection tools to MCP-compatible clients like Claude Desktop.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

A simple note-taking MCP server that allows adding notes and summarizing them via a prompt.

A full-featured secure MCP server for local file system operations, with built-in image processing, OCR and media tools. Fully compliant with the official Model Context Protocol specification, offering standardized request/response schemas, large-file streaming I/O, multi-transport remote deployment, and comprehensive text search & replace functionality for LLM agent integration.