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

VibeTest encompasses a range of tools and platforms focused on enhancing interactions with AI and automating quality assurance (QA) testing for websites. One of the primary offerings is VibeTest.io, which specializes in teaching prompt engineering. This platform provides hands-on coding challenges that help users effectively communicate with AI systems such as Claude and GPT-4, aiming to improve the transformation of code through better prompts (https://vibetest.io/ ) (https://github.com/browser-use/vibetest-use ). On the other hand, the Vibetest MCP (Multi-Channel Platform) servers automate QA testing by deploying AI agents to identify various website issues, including UI bugs, broken links, and accessibility problems. This system is designed to streamline the testing process by launching multiple browser agents that crawl and evaluate web pages for technical flaws (https://apidog.com/blog/vibetest-use-mcp/ ) (https://www.mcpworld.com/en/detail/9ab49d16442b62a5e1ec9de97e05726d ). The Vibetest-use MCP server specifically focuses on these automated testing capabilities, emphasizing its efficiency in detecting and flagging potential issues (https://github.com/luk1337/VibeTest ). Overall, VibeTest is at the intersection of AI prompt engineering and automated web testing, providing valuable resources for both developers looking to enhance their AI interactions and teams aiming to ensure the quality of their web applications. https://vibetest.io/enterprise https://vibetest.io/ #VibeTest #PromptEngineering #QAAutomation #AITesting #WebTesting #VibeTestIO #Claude #GPT4 #MCP #Selenium #Cypress #AccessibilityTesting #UIBugs #BrokenLinks #AutomatedTesting

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

"AI Landscape 2025" provides a comprehensive overview of various AI tools and agents, categorizing them into 14 distinct groups such as AI Agent Builders, Coding, and Productivity, among others. It outlines the number of available tools within each category, highlighting the expansive growth and diversification in the AI sector. The document also notes the pricing models for these AI tools, indicating options for free, paid, and hybrid pricing structures. Key Points - The document categorizes AI tools into 14 different groups including AI Agent Builders, Coding, and Productivity. - A total of 138 tools are dedicated to AI Agent Builders, demonstrating a significant focus on developing intelligent agents. - There are 94 tools available for coding, showcasing the increasing integration of AI in software development. - Productivity tools number 43, indicating a growing market for AI-driven efficiency solutions. - Categories like Finance and Marketing have 16 and 22 tools respectively, reflecting AI's penetration into business operations. - The document mentions different pricing structures: free, paid, and a combination of both for various tools. - A diverse range of applications is identified, from Customer Service (39 tools) to Digital Workers (41 tools), emphasizing the versatile uses of AI technologies. https://aiagentslist.com/ai-agents-map https://aiagentslist.com/mcp-servers #AILandscape2025 #AITools #AIAgents #AIAgentBuilders #AICodingTools #AIProuctivityTools #FinanceAI #MarketingAI #CustomerServiceAI #DigitalWorkers #AIpricing #FreeAI #PaidAI #HybridAI #GPTs #AutoGPT #BabyAGI #AIgrowth #AIadoption

Desktop Commander is an open-source tool that allows terminal command execution and file editing within the Claude Desktop app. It functions as an MCP (Master Control Program) tool, enabling desktop operations based on prompts. It's a popular tool, especially on Smithery. https://desktopcommander.app/ #DesktopCommander #Claude #Smithery #MCP #MasterControlProgram #OpenSource #Terminal #FileEditing #DesktopApps #Automation #Raycast #Alfred #CommandBar #Productivity #AIWorkflow

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

So Augment offers a Context Engine, MCP integrations, Persistent Memory and more ... Try it here its free (for about 50 messages a month ...now where have l heard of that huh Cursor and Windsurf ???) https://www.augmentcode.com/ And the announcmeent made in April this year is in this article here: https://www.augmentcode.com/blog/meet-augment-agent #augment #augmentcode #contextengine #mcp #persistentmemory #aicoding #aidevelopment #cursor #windsurf #codecompletion #ai #codingtools #softwaredevelopment #codingassistant #freecodingtools

How l switched back to Augment Code from Claude Code ! Tried new Claude Code ... verdict: Worth every penny love the little to-do lists but hell lot expensive ! So what do l do l head back home to the loving arms of Augment Code ... still the best and always will be ! (For now 🤫 ... you know relationships nowadays) So this article exaplins why they are nota big fan of Model Pickers ... makes sense though would be great to have the ooption still !). Here is a low done on Augment code and its recent updates: Augment Code is considered a top AI coding agent due to its advanced context engine, which enables personalized and efficient code generation, and its seamless integration with popular IDEs. It also boasts features like memory persistence, which allows it to adapt to individual coding styles, and Multi-Context Programming (MCP) for connecting to various tools and systems, enhancing its utility in the development workflow. Here's a more detailed breakdown of why Augment Code stands out: 1. Contextual Awareness and Memory: Context Engine: Augment's Context Engine is a key differentiator. It analyzes the entire codebase in real-time, providing context-aware suggestions and code completions, leading to more accurate and relevant AI-driven code generation. Memory Persistence: The platform remembers your coding style and project patterns, ensuring that its suggestions are tailored to your preferences and codebase over time, improving efficiency and reducing errors. MCP (Multi-Context Programming): Augment Code goes beyond just the code by integrating with various tools and systems, such as Vercel, Cloudflare, and more, allowing it to gather more information, automate tasks, and even fix issues in live systems. 2. IDE Integration and Workflow: Seamless Integration: Unlike some AI coding tools that require a separate editor, Augment Code integrates directly with popular IDEs like VS Code, JetBrains, Vim, and GitHub, allowing developers to leverage its AI capabilities within their familiar environment. Code Checkpoints: Augment Code automatically tracks changes and creates checkpoints, enabling easy rollback and providing peace of mind when the agent tackles complex tasks. Remote Agent Functionality: Augment Code can operate in a separate container, allowing developers to work on code even when their main machine is off or unavailable, and even run multiple agents in parallel. 3. Advanced Features and Capabilities: Multi-Modal Support: Augment Code can handle various inputs, including screenshots and Figma files, making it helpful for implementing UI elements and debugging visual issues. Terminal Interaction: Beyond code editing, Augment Code can run terminal commands, streamlining tasks like installing dependencies or running dev servers. Auto Mode: For a more streamlined experience, Augment Code offers an Auto Mode, where it automatically applies suggested changes without requiring explicit confirmation for each action. 4. Focus on Collaboration and Productivity: Developer-Centric: Augment Code is designed to work alongside developers, enhancing their existing workflow rather than replacing it, making it a collaborative rather than a replacement tool. Time Savings: By automating tasks, providing accurate suggestions, and handling repetitive coding tasks, Augment Code frees up developers' time to focus on more complex and creative aspects of their work. Continuous Improvement: Through feedback loops and learning from user interactions, Augment Code continuously improves its performance and adapts to the evolving needs of developers. https://www.augmentcode.com/blog/ai-model-pickers-are-a-design-failure-not-a-feature #augmentcode #claude #aicodingagent #aicode #vscode #jetbrains #vim #github #ideintegration #codingtools #productivitytools #memorypersistence #contextengine #multicontextprogramming #vercel #cloudflare #codecheckpoints #remotework #multimodal #figma #terminalinteraction #automode #developercentric #aitools #aidesign #coding #softwaredevelopment #aitool