"A guide to PostgreSQL architecture and internals" matching MCP servers:

Enables a browser agent to inspect, rank, preview, evaluate, and validate transformer layer pruning proposals, while ensuring only a person can commit removals.

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.

Scans AWS environments and generates professional architecture diagrams showing VPC networking, compute, storage, and security resources.

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.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

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.

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.

A secure PostgreSQL MCP server with built-in SSH tunneling that enables AI assistants to connect to databases through bastion hosts automatically, supporting both STDIO and Streamable HTTP transports.

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.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

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.

提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器，支持盘中即时更新及批量查询。

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 coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI assistants to safely interact with PostgreSQL databases, perform queries, inspect schemas, and analyze query performance.

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

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

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

Provides comprehensive PostgreSQL database access with 36 tools for querying, managing schemas, JSONB operations, and database administration. Includes security features like query validation, rate limiting, SSL/TLS support, and optional write operations.

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.

Enables AI assistants to perform read-only PostgreSQL DBA analysis and monitoring through natural language, covering performance, bloat, locks/deadlocks, autovacuum, and schema inspection across PostgreSQL 12-18 without required extensions.

Enables AI assistants to perform read-only PostgreSQL DBA work across versions 12–18, including performance analysis, slow query identification, bloat detection, lock and deadlock monitoring, autovacuum and schema inspection, and replication/WAL checks via natural language. Works with regular user permissions on RDS/Aurora without requiring any extensions, while optionally leveraging pg_stat_statements and pg_stat_monitor for deeper query analytics.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Enables AI assistants to perform PostgreSQL database operations and monitoring through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum checks, and schema inspection across PostgreSQL 12–18 without extensions.