MarkItDown - Make any document AI friendly (by microsoft) MarkItDown is a Python utility designed for converting various file types—including PDFs, Word documents, and images—into Markdown format, emphasizing compatibility with Large Language Models (LLMs) for text analysis. This tool supports a wide range of formats while maintaining essential document structures, as well as integrating seamlessly with existing LLM applications through its Model Context Protocol (MCP). Recent updates introduced breaking changes that require users to adapt their implementations, particularly concerning file handling and dependencies. https://github.com/microsoft/markitdown Someone created a pallatform for this here: https://markitdown.pro/ #MarkItDown #Microsoft #Python #LLM #LargeLanguageModels #Markdown #DocumentConversion #AI #TextAnalysis #ModelContextProtocol #PDFtoMarkdown #WordtoMarkdown #Imagetomarkdown #markitdownpro #Langchain #LlamaIndex #DataConnectors #AIworkflows

Ryan Carson is a five-time founder who has spent the past 20 years building, scaling, and selling startups. In this episode, he shares his playbook for using AI to build products, turning “vibe coding” into a structured and scalable approach that can replace full engineering teams. What you’ll learn: 1. A simple three-file system that transforms chaotic AI coding into a structured, reliable process 2. How to create AI-generated PRDs and task lists that actually work 3. A step-by-step workflow using Cursor to build features systematically 4. Why slowing down to provide proper context is the secret to speeding up your AI development 5. How to use model context protocols (MCPs) to extend your AI’s capabilities beyond just coding 6. Why founders can now build entire companies with minimal engineering teams and how Ryan is doing it himself https://youtu.be/fD4ktSkNCw4?si=cbVp__wJrmyEPObt https://www.ryancarson.com/about https://github.com/snarktank/ai-dev-tasks Tools referenced: • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Gemini 2.5 Pro: https://deepmind.google/models/gemini/pro/ • Repo Prompt: https://repoprompt.com/ • Task Master: https://github.com/eyaltoledano/claude-task-master/blob/main/docs/tutorial.md • Browserbase: https://browserbase.com/ • Stagehand: https://docs.stagehand.dev/integrations/mcp-server #AICoding #RyanCarson #VibeCoding #ChatGPT #Claude #Gemini2.5Pro #RepoPrompt #TaskMaster #Browserbase #Stagehand #Cursor #AIAgent #ProductDevelopment #NoCode #LowCode #EngineeringTeams #PRD #ModelContextProtocols #AIWorkflow #SoftwareDevelopment #AIDrivenDevelopment #ThreeFileSystem #StructuredCoding #AIScaling

A Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to n8n node documentation, properties, and operations. Deploy in minutes to give Claude and other AI assistants deep knowledge about n8n's 525+ workflow automation nodes. n8n-MCP is a Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to n8n node documentation, properties, and operations. It enables AI models like Claude to understand and work with n8n's 525+ workflow automation nodes effectively. Main Function Points - Provides structured access to 528 n8n nodes with 99% coverage of node properties and 63.6% coverage of available actions - Includes 90% coverage of official n8n documentation, including 263 AI-capable nodes - Offers a range of tools for node discovery, configuration, validation, and workflow management - Supports multiple deployment options, including Docker, npx, local installation, and one-click cloud deployment https://youtu.be/5CccjiLLyaY?si=iMKzHb24xQSJ6SMZ https://www.n8n-mcp.com/ https://github.com/czlonkowski/n8n-mcp #n8nMCP #MCP #ModelContextProtocol #n8n #Claude #AIassistant #workflowautomation #nocode #lowcode #AIDevelopment #APIintegration #automation #Docker #npx #LangChain #Zapier #IFTTT

Am sure you thinking of cost saving/cutting costs when using Claude Code here is a tool to consider (thanks @sciencedegen): Zen MCP is a Model Context Protocol server that orchestrates multiple AI models as a development team, allowing Claude to seamlessly collaborate with different models like Gemini, O3, and others to enhance code analysis, problem-solving, and collaborative development. It provides guided workflows, multiple AI perspectives, automatic model selection, and advanced features like context revival, large prompt handling, and web search integration. https://github.com/BeehiveInnovations/zen-mcp-server #zenmcp #claude #gemini #o3 #modelcontextprotocol #aimodelcollaboration #aicoding #aiteam #codedevelopment #promptengineering #costsavings #github #codeanalysis #problem solving

In this theater session, Software Engineer Eleanor Boyd walks through building a custom MCP (Model Context Protocol) server in Visual Studio Code using GitHub Copilot and Python. She walks through a real use case, fetching PyPI package data, and shows how to connect your tool to Copilot’s Agent Mode for powerful AI-assisted coding. #MCP #ModelContextProtocol #VisualStudioCode #GitHubCopilot #Python #PyPI #AIAssistedCoding #AgentMode #SoftwareEngineering #CodeDevelopment #AItools #Codegen #CodeCompletion #Tabnine #AmazonCodeWhisperer #JetBrainsAIAssistant https://youtu.be/SYcQXozpb_E?si=8QgX0-7lr3WsA0ZJ

🚀 Unlock the Power of Model Context Protocol (MCP) with Sampling! 🌟 In the latest installment of the MCP crash course, we dive into sampling, one of the most powerful features of the protocol. This innovative approach allows servers to delegate tasks back to the client's LLM, enabling a seamless integration of AI functionalities without overwhelming server resources. Key Highlights: Bidirectional Architecture: While LLM clients typically invoke server logic, sampling lets servers request input from the client’s AI model, creating a more efficient workflow. Cost Efficiency: By transferring the burden of AI computation to the client, it reduces server load and associated costs. Flexibility & Scalability: Clients can choose their preferred models for different requests, which enhances application scalability and user customization. By implementing sampling, developers can build better, more responsive AI-driven applications. Discover how to optimize your MCP servers and improve the overall performance with practical examples and best practices in the full article! #AI #MachineLearning #TechInnovation #ModelContextProtocol #MCP #Sampling #ServerSideLogic #LLM #OpenSource #DevCommunity https://www.dailydoseofds.com/model-context-protocol-crash-course-part-5/