what is awesome-ai-stack fr?

awesome-ai-stack is a small command-line tool that helps you install and wire up extras for AI coding assistants. It runs as a terminal UI, lets you browse a curated catalog of add-ons, and then writes the matching configuration into your client app so the new tools show up automatically. The catalog covers three kinds of things. MCP servers, which are programs that AI assistants can talk to over the Model Context Protocol, include Context7, Browser Use, Firecrawl, GitHub MCP, and Perplexity MCP. Memory layers, which give the assistant a way to remember things across chats, include Claude Mem, Mem0, and Zep Memory. There is also a category called skills, with one entry called UIUX ProMax. The README does not invent extra detail about what each one does beyond naming it. To run it you type npx awesome-ai-stack in a terminal. The flow is short: pick a role such as Developer, Marketer, Researcher, or Designer, or browse all tools, multi-select the packages you want with checkboxes, choose which client you are configuring, which can be Claude Desktop, Cursor, Windsurf, or an install-only mode, then confirm. MCP servers are config-only, meaning the client runs them through npx based on the written config, while memory and skills entries are installed through npx or npm. Config snippets are deep-merged into your existing client config, and the README says existing keys are never overwritten. The tool knows the standard config file locations for each target. For Claude Desktop it writes to the platform-specific path under Application Support on macOS, ~/.config/Claude on Linux, or APPDATA on Windows. For Cursor it writes to ~/.cursor/mcp.json. For Windsurf it writes to ~/.codeium/windsurf/mcp_config.json. For development the README shows the usual clone, npm install, npm run validate to check the registry JSON files, and npm start to launch the TUI. There is an environment variable AWESOME_AI_STACK_USE_LOCAL that forces reading the local packages and roles directories. Contributing a new tool is described as adding a JSON file. The project is MIT licensed and the repository has 2 stars at the time of writing.