GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. ActionKit by Paragon - Connect to 130+ SaaS integrations (e.g. Slack, Salesforce, Gmail) with Paragon’s ActionKit API. Adfin - The only platform you need to get paid - all payments in one place, in
DevRel Guide by Rohit Ghumare Istio Guru by Rohit Ghumare BabyAgi.txt by Nicholas Dobos Take Code Captures by oscaramos.dev Diffusion Master by RUSLAN LICHENKO YT transcriber by gpt.swyx.io 科技文章翻译 by Junmin Liu genz 4 meme by ChatGPT Math Mentor by ChatGPT Interview Coach by Danny Graziosi The Negotiator by ChatGPT Sous Chef by ChatGPT Tech Support Advisor by ChatGPT Sticker Whiz by ChatGPT Obscri
Everything a developer needs to know about Generative AI for SaaS
Everything a developer needs to know about Generative AI for SaaS Few months ago, I knew almost nothing about AI. I used ChatGPT and Co-Pilot (I'm civilized, after all), but a lot of the content around AI was Greek to me. Terms like models, transformers, training, inference, RAG, attention, and agents were unfamiliar. Last week, I have completed my first end-to-end AI-based product: AI Code Assist
LLM Evaluation Metrics: The Ultimate LLM Evaluation Guide - Confident AI
It is no secret that evaluating the outputs of Large Language Models (LLMs) is essential for anyone building robust LLM applications. Whether you're fine-tuning for accuracy, enhancing contextual relevance in a RAG pipeline, or increasing task completion rate in an AI agent, choosing the right evaluation metrics is critical. Yet, LLM evaluation remains notoriously difficult—especially when it come
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GitHub - linexjlin/GPTs: leaked prompts of GPTs