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Source channel @githubtrending · Post #15076 · Aug 19

#python#aws#mcp#mcp_client#mcp_clients#mcp_host#mcp_server#mcp_servers#mcp_tools#modelcontextprotocol AWS MCP Servers use the Model Context Protocol (MCP), an open standard that connects AI tools with AWS data and services in a simple, secure way. These servers improve AI responses by providing up-to-date AWS documentation, best practices, and workflow automation for cloud development, infrastructure, and operations. You can run MCP servers locally for development or use AWS-managed remote servers for easy access and scalability. MCP servers support many AWS services like Lambda, DynamoDB, EKS, and more, helping you build, manage, and optimize AWS resources efficiently with AI assistance. Installation is easy with one-click options for popular tools like VS Code and Cursor. This makes cloud development faster, more accurate, and cost-effective. https://github.com/awslabs/mcp

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@githubtrending · Post #14897 · 07/02/2025, 01:00 PM

#python#ernie#ernie_45#ernie_45_vl#erniekit#llm#vlm ERNIE 4.5 is a powerful AI model family that understands and generates text, images, and videos together, thanks to its special design that shares knowledge across these types without losing quality. It includes large models with billions of parameters and smaller efficient ones, all trained using the PaddlePaddle framework for fast and effective use. ERNIE 4.5 excels in tasks like language understanding, visual reasoning, and following instructions, often outperforming other top models. It also offers tools for easy training and deployment on various hardware. This means you can use ERNIE 4.5 for advanced AI applications involving text and visuals with high accuracy and efficiency, supported by open-source resources for customization and development[1][3][5]. https://github.com/PaddlePaddle/ERNIE