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Source channel @githubtrending · Post #14793 · Jun 5

#python#agents#ai#ai_agents#llm#llms#mcp#model_context_protocol#python The Model Context Protocol (MCP) is a standard way for AI agents to connect with different tools and data sources, making it much easier to build powerful AI applications without writing custom code for each integration[2][5]. The mcp-agent framework uses MCP to let you quickly create agents that can do things like read files, fetch web pages, or manage emails, and you can combine these agents in flexible ways to handle complex tasks. This means you can focus on what you want your AI to do, while mcp-agent takes care of connecting to the right tools and managing the workflow, saving you time and effort[3][5]. https://github.com/lastmile-ai/mcp-agent

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@githubtrending · Post #14904 · 07/03/2025, 12:00 PM

#go#ai_assistant#ai_generated_code#cloud_native#code_generation#custom_templates#developer_tools#development_framework#gin#go_sponge#golang#grpc#grpc_gateway#low_code#microservice#protobuf#restful_api#sponge#web Sponge is a powerful Go development framework that helps you quickly build backend services like RESTful APIs and microservices with minimal coding. It generates modular Go code automatically by parsing SQL, Protobuf, and JSON files, letting you create complete backend projects through a simple web interface without complex commands. Sponge supports custom templates and integrates AI assistants (like ChatGPT) to help write business logic, greatly speeding up development and reducing repetitive work. It also offers full support for testing, API docs, and deployment, making your project more stable, efficient, and easier to maintain. This saves you time and improves code quality. https://github.com/go-dev-frame/sponge

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture