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Open Source: #awesome-list
Catalog projects marked with #awesome-list. Tags work as dedicated landing pages, so related tools are easier to find and connect.
This collection holds 37 projects with a combined 4,154,972 GitHub stars. Main languages: Python, JavaScript, Markdown.
About the awesome lists
Awesome lists are a GitHub phenomenon: carefully curated collections of the best resources on a topic, maintained by communities for years. A good awesome list saves weeks of solo research.
Collected here are the most valuable of them. This is the catalog's meta level: each list is itself a guide to hundreds of vetted tools and materials in its field.
Repositories
Awesome is the original awesome-list catalog: curated lists of useful resources across software, development, and many adjacent technology topics.
Awesome Python is a curated list of Python frameworks, libraries, tools, and resources across the Python ecosystem.
Awesome Selfhosted is a large catalog of free software self-hosted services and web applications for running on your own server.
The Book of Secret Knowledge is a large collection of cheatsheets, manuals, one-liners, security/devops resources, and practical engineering links.
Awesome Go is a curated list of Go libraries, frameworks, tools, and resources across the Go ecosystem.
prompts.chat is an open source AI prompt library that grew from Awesome ChatGPT Prompts and is available as a website and self-hosted project.
Awesome Hacking is a large collection of security resources covering penetration testing, malware analysis, and related topics.
Awesome Mac is a large catalog of macOS applications organized by category: editors, office, development, media, utilities, and more.
Awesome DESIGN.md is a collection of DESIGN.md files and design-system analyses from popular brands for AI agents and teams generating interfaces.
Awesome MCP Servers is a catalog of MCP servers for connecting AI agents to files, databases, browsers, SaaS products, and developer tools.
Awesome for Beginners is a curated list of projects with beginner-friendly issues for a first open source contribution across languages and ecosystems.