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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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@githubtrending · Post #15173 · 09/27/2025, 12:30 PM

#cplusplus#c_plus_plus#cpp#datachannel#libdatachannel#libnice#p2p#peer_to_peer#peerconnection#rfc_8831#rfc_8834#rtcdatachannel#rtcpeerconnection#sctp#webrtc#webrtc_datachannel#webrtc_video#websocket libdatachannel is a lightweight, easy-to-use C/C++ library that lets you add real-time peer-to-peer data, media, and WebSocket communication to your apps across many platforms like Linux, Windows, macOS, Android, and iOS. It simplifies WebRTC by providing a smaller, simpler alternative to Google's library, with compatibility for browsers like Firefox and Chrome. You can use it to connect native apps directly to web browsers with minimal dependencies, supporting secure connections via GnuTLS, Mbed TLS, or OpenSSL. It also supports compiling to WebAssembly for browser use, making it flexible for cross-platform real-time communication development[1][4]. This helps you build fast, efficient apps for video, audio, or data sharing without heavy libraries. https://github.com/paullouisageneau/libdatachannel