"Guide to Reading and Writing Data with PostgreSQL" matching MCP servers:

A production-oriented MCP server for PostgreSQL that exposes database operations like query execution, schema introspection, and table metadata to MCP clients such as Claude Desktop and VS Code.

A secure MCP server that lets AI assistants directly interact with PostgreSQL databases via tools like create_table, list_tables, and execute_sql, plus a web configurator for managing connections.

Content writing toolkit for headline generation, readability scoring, tone analysis, outline building, and plagiarism similarity checking.

Read-only MCP server for PostgreSQL, enabling schema discovery, table metadata, and safe SELECT queries via READ ONLY transactions.

A production-ready MCP server that connects AI assistants to any PostgreSQL database with 25 tools and role-based access control.

Provides AI-driven PostgreSQL database management with secure OAuth 2.1 authentication, enabling users to administer, monitor, and query databases with support for extensions like pgvector, PostGIS, and pg_cron.

An MCP server that enables a private mobile-first reading experience in ChatGPT, managing multi-book shelves, reading progress, highlights, thoughts, and bookmarks, with secure cloud storage and AI co-reading of the current page.

Enables users to interact with PostgreSQL databases through natural language, with GitHub OAuth authentication and role-based access control.

A Model Context Protocol server that provides read-only access to PostgreSQL databases. This server enables LLMs to inspect database schemas and execute read-only queries.

Provides comprehensive design principles and best practices to help LLMs generate modern, accessible web pages through guidance on layouts, colors, and typography. It enables users to review design approaches and access expert recommendations for responsive design, component structure, and current industry trends.

A Model Context Protocol server that enables powerful PostgreSQL database management capabilities including analysis, schema management, data migration, and monitoring through natural language interactions.

Facilitates management and optimization of PostgreSQL databases, offering analysis, setup guidance, and debugging, while ensuring secure and efficient database operations.

Enables natural language interaction with PostgreSQL databases through Amazon Q for querying data, listing tables, and describing schemas. It provides secure, read-only access with automatic row limits to ensure efficient database exploration.

Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.

A Python MCP server that enables schema discovery, read-only SQL queries, table previews, and index/relationship analysis on PostgreSQL databases.

Enables AI agents to interact with PostgreSQL databases through the Model Context Protocol, supporting SQL queries, schema management, and data operations.

A wrapper for mcp-remote that provides secure authentication for protected MCP servers using Adobe IMS or Okta OAuth flows. It features automated token management, validation, and background refreshing for seamless access to remote resources.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables secure, read-only PostgreSQL database interaction through natural language, with automatic database discovery and connection management.

Enables AI agents to interact with PostgreSQL databases over HTTP/JSON-RPC, supporting SQL queries, schema introspection, table/index analysis, EXPLAIN query planning, role and privilege inspection, and database monitoring.