SQL Database Bridge
Provides a bridge to SQL databases (MSSQL, MySQL, PostgreSQL) for executing queries, exploring schem...
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View All →Supabase MCP Server
Connect Supabase projects directly with AI assistants using the Model Context Protocol (MCP). This server standardizes communication between Large Language Models and Supabase, enabling AI to manage tables, query data, and interact with project features like edge functions, storage, and branching. Customize access with read-only or project-scoped modes and select specific tool groups to fit your needs. Integrated tools cover account management, documentation search, database operations, debugging, and more, empowering AI to assist with development, monitoring, and deployment tasks in your Supabase environment efficiently and securely.
Postgres MCP Pro
Boost your Postgres database performance with Postgres MCP Pro, an AI-driven MCP server offering advanced index tuning, detailed explain plans, and comprehensive health checks. It combines proven optimization algorithms with schema intelligence for safe, context-aware SQL execution. Whether analyzing slow queries or recommending optimal indexes, Postgres MCP Pro empowers developers to improve efficiency and maintain database integrity. Designed for both development and production, it supports flexible transport options and robust access controls, making database management smarter, safer, and easier. Experience deterministic performance insights alongside AI assistance to keep your Postgres running at its best.
More for Monitoring
View All →macOS Tools
Provides macOS system monitoring with SQLite-based historical data storage and enhanced file search with tagging support, collecting real-time CPU, memory, disk, and network metrics while offering content-based file searching with regex support and macOS file tagging operations through native utilities like Spotlight and extended attributes.
Dual-Cycle Reasoner
Provides dual-cycle metacognitive reasoning framework that detects when autonomous agents get stuck in repetitive behaviors through statistical anomaly detection and semantic analysis, then automatically diagnoses failure causes and generates recovery strategies using case-based learning.