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Source channel @githubtrending · Post #15066 · Aug 16

#python#agents#ai#api_gateway#asyncio#authentication_middleware#devops#docker#fastapi#federation#gateway#generative_ai#jwt#kubernetes#llm_agents#mcp#model_context_protocol#observability#prompt_engineering#python#tools The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure. https://github.com/IBM/mcp-context-forge

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djangoproject

@djangoproject · Post #336 · 05/09/2017, 05:24 AM

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https://dzone.com/articles/pyflakes-passive-checker There are several code #analysis tools for Python. The most well known is pylint. Then there’s pychecker and now we’re moving on to #pyflakes. The pyflakes project is a part of something known as the Divmod Project. Pyflakes doesn’t actually execute the code it checks, unlike #pychecker. Of course, #pylint also doesn’t execute the code. Regardless, we’ll take a quick look at it and see how pyflakes works and if it’s better than the competition.

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#analysis #pyflakes #pychecker #pylint