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Source channel @githubtrending · Post #14935 · Jul 9
#other#clients#mcp The Model Context Protocol (MCP) is an open standard that lets AI models easily and securely connect to different data sources and tools, making it much simpler for developers to build smart apps that can access files, databases, and APIs without custom code for each one[2][3][4]. There are many free and easy-to-use MCP clients—like desktop apps, web apps, and command-line tools—that let you quickly add new AI features and automate tasks, so you can get more done with less effort and technical hassle. This means you can use AI to help with coding, data analysis, and daily work, all while keeping your data safe and your setup flexible[2][3][4]. https://github.com/punkpeye/awesome-mcp-clients
Search: #asynchronously
@djangoproject · Post #585 · 03/23/2018, 02:43 AM
https://www.fullstackpython.com/celery.html #Celery is a task #queue implementation for Python web applications used to #asynchronously execute work outside the HTTP request-response cycle.
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@djangoproject · Post #262 · 02/16/2017, 07:24 AM
http://masnun.com/2015/11/20/python-asyncio-future-task-and-the-event-loop.html On any platform, when we want to do something #asynchronously, it usually involves an #event loop. An event loop is a loop that can register #tasks to be executed, execute them, delay or even cancel them and handle different events related to these operations. Generally, we #schedule multiple async functions to the event loop. The loop runs one function, while that function waits for #IO, it pauses it and runs another. When the first function completes IO, it is resumed. Thus two or more functions can #co_operatively run together. This the main goal of an event loop.