The full-stack TypeScript framework to build, test, and deploy production-ready MCP servers and AI-native apps.

A modern, container-friendly, optionally-distributed, fault-tolerant, highly available, leader-electing, highly configurable, precompiled, multi-architecture, portable, security-hardened, production-ready cron replacement

Generate production-ready Python and AI stacks by combining frameworks, data engines, tooling, and cloud deployment.

Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents

Model Context Protocol (MCP) servers for managing homelab infrastructure through Claude Desktop. Monitor Docker/Podman containers, Ollama AI models, Pi-hole DNS, Unifi networks, and Ansible inventory. Includes security checks, templates, and automated pre-push validation. Production-ready for homelabs.

A curated, DevOps-focused list of Model Context Protocol (MCP) servers—covering source control, IaC, Kubernetes, CI/CD, cloud, observability, security, and collaboration—with a bias toward maintained, production-ready integrations.

A comprehensive toolkit for deploying production-ready Generative AI infrastructure on Amazon EKS. Includes pre-configured components for: 🚀 AI Gateway (LiteLLM) 🤖 LLM Serving (vLLM, SGLang, Ollama) 📊 Vector Databases, 🔍 Embedding Models (TEI) 📈 Observability (Langfuse, Phoenix) etc. Fast-track your GenAI deployment with Kubernetes

Express REST API and MCP Server Framework is a comprehensive development framework for building RESTful APIs and MCP servers with Express.js. It provides a complete template for creating production-ready APIs using Node.js, Express, Mongoose (MongoDB), and Sequelize (SQL databases).