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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
Search: #xmlrpc
@djangoproject · Post #408 · 08/10/2017, 10:42 AM
https://docs.python.org/3/library/xmlrpc.html #XML-#RPC is a #Remote_Procedure_Call method that uses XML passed via #HTTP as a transport. With it, a #client can call methods with parameters on a remote server (the #server is named by a URI) and get back structured data. #xmlrpc is a package that collects server and client modules implementing XML-RPC. The modules are: xmlrpc.client xmlrpc.server