#javascript #ai #cursor #cursor_ai #cursorai #lovable #lovable_dev #roocode #task_manager #tasks #tasks_list #windsurf #windsurf_ai

Task Master is a tool that helps manage tasks using AI. It works with different AI models like Claude and supports various providers such as OpenAI and Anthropic. Users can set up tasks, track progress, and even switch between AI models easily. This tool is useful for developers who need to organize their work efficiently and want flexibility in choosing the best AI model for their projects. It helps streamline tasks and improve productivity by automating some processes and providing clear guidance on what to do next.

https://github.com/eyaltoledano/claude-task-master

#other #ai #bolt #copilot #cursor #cursorai #devin #devinai #github_copilot #lovable #open_source #replit #system_prompts #trae #trae_ai #trae_ide #v0 #vscode #windsurf #windsurf_ai

You can access a huge collection of over 7000 lines of official system prompts and internal tools from many AI models and agents like v0, Manus, Cursor, Replit Agent, and more. These prompts guide AI to work better by giving clear instructions, which helps the AI give more accurate and useful answers. Using these prompts can save you time, improve AI performance, and make your interactions with AI smoother and more productive. Plus, there’s a free AI security audit service to help protect your AI systems from leaks and hacks, keeping your data safe. Supporting this project helps keep these valuable resources updated.

https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools

#python #ai #authentication #authorization #claude #cursor #fastapi #llm #mcp #mcp_server #mcp_servers #modelcontextprotocol #openapi #windsurf

FastAPI-MCP is a tool that lets you easily turn your FastAPI web API endpoints into Model Context Protocol (MCP) tools, which AI agents can use directly. It requires almost no setup—just connect it to your FastAPI app, and it automatically preserves your request/response data models and documentation. It also includes built-in authentication using your existing FastAPI security methods. You can run the MCP server inside your app or separately, and it communicates efficiently using FastAPI’s ASGI interface. This makes it simple to integrate AI capabilities with your existing FastAPI services without rewriting code, saving you time and effort while keeping your API secure and well-documented[1][5].

https://github.com/tadata-org/fastapi_mcp