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Source channel @githubtrending · Post #14896 · Jul 2

#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

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

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#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