Built an MCP server for .NET developers working with AI

What it does: ## The key difference: ## Currently tracking: If you're building AI applications with .NET or constantly learning, you've noticed LLMs confidently give you code that doesn't compile or completely wrong explanations about how things work. I got tired of it, so I built DotNet AI MCP Server. ** Connects your favorite client to two sources: Live GitHub repos - Semantic Kernel, OpenAI .NET SDK, MCP C# SDK, AutoGen, and more. Real code and documentation from the actual repos. Microsoft Learn - I proxied the official Microsoft Learn MCP tools but optimized them: better token efficiency, clearer descriptions, and improved argument names so the LLM actually picks the right tool. ** Zero prompt engineering. Just ask your question naturally - "How do Semantic Kernel agents work?" or "Show me how to build an MCP server with C#" - and the tools trigger automatically. No need to tell it "use this tool" or "search the documentation" like other MCP servers require. It uses progressive file exposure (repos → folders → files → content) which saves tokens and doesn't flood your context with irrelevant data. ** AI Frameworks & LLM SDKs: Semantic Kernel • AutoGen • Kernel Memory • OpenAI .NET • Google Gemini • Anthropic Claude • MCP C# SDK • LangChain.NET • OllamaSharp Vector Database C# SDKs: Pinecone • Qdrant • Weaviate • Redis Stack Setup takes 30 seconds. If it helps, drop a ⭐ so other .NET devs can find it. Try it: https://github.com/Ahod26/dotnet-ai-mcp-server Roast me if it sucks. 🔥 Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse - Live GitHub repos - Semantic Kernel, OpenAI .NET SDK, MCP C# SDK, AutoGen, and more. Real code and documentation from the actual repos. - Microsoft Learn - I proxied the official Microsoft Learn MCP tools but optimized them: better token efficiency, clearer descriptions, and improved argument names so the LLM actually picks the right tool.