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Source channel @githubtrending · Post #15102 · Aug 29

#csharp The Model Context Protocol (MCP) is an open standard that lets AI models connect easily and securely to external data sources and tools, like business systems or cloud services. It acts like a universal adapter, enabling AI to access the right context and data to perform tasks accurately and efficiently. Microsoft offers many MCP servers that link AI with services such as Azure DevOps, SQL databases, Microsoft 365, and more, allowing AI to interact naturally with your data and workflows. This helps you get smarter AI assistance, better automation, and easier integration across your tools. https://github.com/microsoft/mcp

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@githubtrending · Post #14772 · 06/01/2025, 12:00 AM

#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4]. https://github.com/dragonflydb/dragonfly