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

The Apify Model Context Protocol (MCP) Server serves as an interface for AI applications to integrate with Apify's library of Actors for efficient web scraping and automation tasks. Users can access this server through secure HTTPS endpoints or the standard input/output method for local integrations. The MCP framework additionally allows dynamic actor management, facilitating real-time addition and execution of various Actors to enhance the capabilities of AI agents. Key Points - The Apify MCP Server connects AI applications with Apify's library of Actors for real-time web scraping and automation. - Users can connect to the MCP Server via HTTPS with OAuth or through standard input/output methods for local setups. - Before using the MCP Server, users must have an Apify account, API token, and an MCP-compatible client. - The server allows for dynamic actor management, enabling AI agents to discover, add, and execute Actors as needed. - Users can interact with the MCP Server over Server-Sent Events (SSE) for message sending and response receiving. - Troubleshooting tips include verifying the API token, ensuring the server runs the latest version of the MCP library, and ensuring a suitable Node.js environment. - Users can utilize a web-based Tester MCP Client for an accessible alternative to integrate and test capabilities without local setup. https://docs.apify.com/platform/integrations/mcp https://github.com/apify/actors-mcp-server #Apify #MCP #actors #webscraping #automation #AIagents #dynamicactormanagement #serversentevents #SSE #nocode #lowcode #rapiddevelopment #TesterMCPClient #webautomation #apifyactors #cloudcomputing #python #nodejs #portkey #airtable

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

Anthropic Academy - Build with Claude Start developing Claude-powered applications with our comprehensive API guides and best practices https://www.anthropic.com/learn/build-with-claude What you learn (Explore by topic) - Claude 4 Learn how to harness the intelligence and capability of our latest models, Claude Sonnet 4 and Claude Opus 4 - APIs & SDKs Learn about Anthropic's APIs, SDKs, and other development tools - Agents Build autonomous agents and agentic systems that understand, plan, and execute complex tasks - Model Context Protocol (MCP) Build advanced applications with the Model Context Protocol - Claude Code Speed up your development with Claude Code - Tool use Extend Claude's capabilities by connecting to external tools and APIs - Extended thinking Improve Claude's ability to solve complex tasks by allowing it to reason - Retrieval augmented generation (RAG) Build effective RAG systems to enhance Claude's responses with external data - Prompt engineering Create effective prompts that maximize Claude's performance - Evaluations Test and improve Claude's performance with structured evaluations - Prompt caching Optimize performance and reduce costs by reusing Claude's responses - Vision Harness Claude's ability to understand and analyze visual information - Computer use Learn how to use Claude models to interact with a computer desktop environment - Hackathon hacker guide Resources to help you get started with Claude, whether you're hacking with us at an event or on your own

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

What is Claudia UI and what can it do for your Vibe Coding ? Claudia is a powerful desktop application that transforms how you interact with Claude Code. It provides a beautiful GUI for managing your Claude Code sessions, creating custom agents, tracking usage, and much more. Claudia serves as a command center for Claude Code, bridging the gap between the command-line tool and a visual experience that makes AI-assisted development more intuitive and productive. Main Function Points - Visual Project Browser: Navigate through all your Claude Code projects - Session History: View and resume past coding sessions with full context - Custom AI Agents: Create specialized agents with custom system prompts and behaviors - Usage Analytics Dashboard: Monitor your Claude API usage and costs in real-time - MCP Server Management: Manage Model Context Protocol servers from a central UI - Timeline & Checkpoints: Create checkpoints at any point in your coding session and navigate through your session history - CLAUDE.md Management: Edit CLAUDE.md files directly within the app with live preview and syntax highlighting https://github.com/getAsterisk/claudia #ClaudiaUI #ClaudeCode #GUI #DesktopApp #AIAssistant #AICoding #VisualIDE #SessionManagement #UsageAnalytics #CustomAIagents #MCPserver #TimelineCheckpoints #CLAUDEmdfiles #OpenAI #CursorAI #GitHubCopilot #AIdevelopment #ProductivityTools

For all the techies ... ever consider how to build your own MCP Server??? Here is a tutorial probably worth it. To build an MCP (Model Context Protocol) server, you'll need to set up a development environment, define tools and resources, and implement the server logic to handle requests from clients. The MCP standard enables AI models to interact with external tools and services, making it easier for agents to access and utilize various functionalities. https://youtu.be/egVm_z1nnnQ?si=34eVdx8fSL6eaaq_ https://dev.to/debs_obrien/building-your-first-mcp-server-a-beginners-tutorial-5fag

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/

https://towardsdatascience.com/model-context-protocol-mcp-tutorial-build-your-first-mcp-server-in-6-steps/