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Source channel @githubtrending · Post #15116 · Sep 3

#other#ai#anthropic_claude#awesome#context#mcp#model_context_protocol#servers#tool_use#tools Model Context Protocol (MCP) is an open standard that lets AI models securely connect to various data sources and tools, like files, databases, APIs, and cloud services, to get real-time, relevant information. This helps AI give more accurate, up-to-date, and context-aware answers, reducing repeated data processing and improving efficiency. MCP also supports automation of complex workflows and integration with many platforms, making AI more powerful and flexible. However, running MCP servers requires careful security measures to avoid risks like unauthorized code execution. Using MCP can save time, reduce costs, and enhance AI capabilities for tasks like chatbots, data analysis, and system control. https://github.com/appcypher/awesome-mcp-servers

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djangoproject

@djangoproject · Post #577 · 03/02/2018, 07:28 PM

http://www.django-rest-framework.org/api-guide/authentication/#tokenauthentication #Authentication is the mechanism of associating an incoming request with a set of identifying credentials, such as the user the request came from, or the token that it was signed with. The permission and throttling policies can then use those credentials to determine if the request should be permitted. #REST framework provides a number of authentication schemes out of the box, and also allows you to implement custom schemes. #Django_REST_Framework#Django#DRF

djangoproject

@djangoproject · Post #589 · 03/29/2018, 06:38 AM

http://books.agiliq.com/projects/django-api-polls-tutorial/en/latest/ Building #APIs with #Django and #Django_Rest_Framework(#DRF) Introductions Setup, Models and Admin A simple API with pure Django #Serializing and Deserializing Data Views and Generic Views More views and viewsets #Access_Control #Testing and Continuous Integeration Testing and Using API with Postman Documenting APIs (with Swagger and more)