A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.
Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.
Enables system automation and control including command execution, process management, network tools, environment variables, disk usage, and service status.
A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.
Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.
MCP server for managing AI prompts with CRUD operations, categorization, and tagging. Enables users to store, organize, and retrieve their favorite prompts efficiently.
A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.
A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.
Creates a local MCP runtime for design-system repositories, enabling AI coding agents to look up and use real components, icons, and tokens instead of guessing.
A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.
Cross-project memory for Claude Code, enabling local semantic recall and secure, git-versioned markdown storage of reusable knowledge across repositories.
Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.
Enables real-time monitoring of system resources including CPU, GPU (NVIDIA, Apple Silicon, AMD/Intel), memory, disk, network, and processes across Windows, macOS, and Linux platforms through natural language queries.