#typescript #agent #browser_use #computer_use #electron #gui_agents #mcp #mcp_server #vision #vite #vlm

Agent TARS is a powerful tool that helps automate tasks using AI. It integrates with many tools and can handle complex tasks like web scraping and data analysis. This makes it easier to manage workflows and reduces errors. Users can automate tasks in just a few steps, making it very efficient. Agent TARS also supports advanced browser operations and has a user-friendly desktop app, which makes it easy to use for anyone. Overall, it helps users save time and work more efficiently.

https://github.com/bytedance/UI-TARS-desktop

#python #ai #authentication #authorization #claude #cursor #fastapi #llm #mcp #mcp_server #mcp_servers #modelcontextprotocol #openapi #windsurf

FastAPI-MCP is a tool that lets you easily turn your FastAPI web API endpoints into Model Context Protocol (MCP) tools, which AI agents can use directly. It requires almost no setup—just connect it to your FastAPI app, and it automatically preserves your request/response data models and documentation. It also includes built-in authentication using your existing FastAPI security methods. You can run the MCP server inside your app or separately, and it communicates efficiently using FastAPI’s ASGI interface. This makes it simple to integrate AI capabilities with your existing FastAPI services without rewriting code, saving you time and effort while keeping your API secure and well-documented[1][5].

https://github.com/tadata-org/fastapi_mcp

#go #github #mcp #mcp_server

The GitHub MCP Server helps developers by connecting AI tools directly to GitHub. This allows AI assistants to manage issues, pull requests, analyze code, and automate workflows using natural language commands. It simplifies tasks like creating pull requests, reviewing code changes, and monitoring CI/CD pipelines. By automating these tasks, developers can focus more on coding and problem-solving, making their work more efficient and productive.

https://github.com/github/github-mcp-server

#python #csharp #java #javascript #javascript_applications #mcp #mcp_client #mcp_security #mcp_server #model #model_context_protocol #modelcontextprotocol #python #typescript

You can learn the Model Context Protocol (MCP), a new standard for connecting AI models with applications, through a free, open-source curriculum that includes hands-on coding examples in C#, Java, JavaScript, Python, and TypeScript. The curriculum covers basics, security, building servers and clients, advanced topics, and best practices, with multi-language support and community help via Discord. You can also join MCP Dev Days, a free online event for deep technical learning and networking. This resource helps you quickly gain practical skills to build and integrate AI tools effectively, boosting your development capabilities in AI workflows.

https://github.com/microsoft/mcp-for-beginners

#python #aws #mcp #mcp_client #mcp_clients #mcp_host #mcp_server #mcp_servers #mcp_tools #modelcontextprotocol

AWS MCP Servers use the Model Context Protocol (MCP), an open standard that connects AI tools with AWS data and services in a simple, secure way. These servers improve AI responses by providing up-to-date AWS documentation, best practices, and workflow automation for cloud development, infrastructure, and operations. You can run MCP servers locally for development or use AWS-managed remote servers for easy access and scalability. MCP servers support many AWS services like Lambda, DynamoDB, EKS, and more, helping you build, manage, and optimize AWS resources efficiently with AI assistance. Installation is easy with one-click options for popular tools like VS Code and Cursor. This makes cloud development faster, more accurate, and cost-effective.

https://github.com/awslabs/mcp

#python #agent #ai #ai_coding #claude #claude_code #language_server #llms #mcp_server #programming #vibe_coding

Serena is a free, open-source toolkit that turns large language models (LLMs) into powerful coding agents able to work directly on your codebase with IDE-like precision. It uses semantic code analysis to understand code structure and symbols, enabling efficient code search and editing without reading entire files. Serena supports many programming languages and integrates flexibly with various LLMs and development environments via the Model Context Protocol (MCP). This means you can automate complex coding tasks, improve productivity, and reduce costs without subscriptions, making your coding workflow faster and smarter.

https://github.com/oraios/serena

#python #agents #ai #ai_agents #api #developer_tools #discord #function_calling #integration #llm #mcp #mcp_client #mcp_server #oauth2 #open_source

Klavis AI helps developers connect AI tools to other services like GitHub, Gmail, and Slack easily. It offers hosted servers that handle authentication and client code automatically, making it simpler to integrate AI with various platforms. This saves time and effort by eliminating the need for custom authentication management and client library maintenance. Users can quickly set up and scale their AI applications without worrying about complex integrations, making it easier to deploy AI-powered workflows securely and efficiently.

https://github.com/Klavis-AI/klavis

#typescript #mcp #mcp_server #n8n #workflows

n8n-MCP is a tool that connects AI assistants like Claude to the n8n workflow automation platform, giving AI deep knowledge of over 500 n8n nodes, their properties, operations, and documentation. It helps you quickly find, configure, and validate workflow templates or build workflows from scratch with real-world examples and smart filtering. You can deploy it easily via npx, Docker, or cloud services. This saves you time, reduces errors, and boosts confidence by letting AI assist in designing and managing complex automations safely, as you test changes before applying them to production. It makes building and maintaining workflows faster and more reliable.

https://github.com/czlonkowski/n8n-mcp

#python #data_analysis #dingtalk_robot #docker #feishu_robot #hot_news #mail #mcp #mcp_server #news #ntfy #python #telegram_bot #trending_topics #wechat_robot

TrendRadar is a lightweight, easy-to-deploy tool that gathers trending topics from 11+ major platforms like Zhihu, Douyin, and Baidu in just 30 seconds. It lets you set custom keywords to filter only news you care about, eliminating information overload. The tool offers three smart notification modes—daily summaries, current rankings, or incremental alerts—and supports multiple channels including WeChat Work, Feishu, DingTalk, Telegram, and email. You can customize how trends are ranked using a personalized algorithm that weighs ranking position, frequency, and hotness. With GitHub Pages for web reports, Docker support, and AI-powered analysis through MCP protocol, TrendRadar transforms scattered platform algorithms into one unified, user-controlled news feed tailored to your interests.

https://github.com/sansan0/TrendRadar

#typescript #browser #chrome #chrome_devtools #debugging #devtools #mcp #mcp_server #puppeteer

Chrome DevTools MCP lets your AI coding tools like Gemini, Claude, or Cursor control a live Chrome browser for automation, debugging, and performance checks. Install it easily with npx chrome-devtools-mcp@latest in your MCP config, then prompt "Check performance of a site" to auto-record traces, take screenshots, analyze networks, and fix issues reliably. This benefits you by making AI smarter at web coding—verifying changes in real-time, spotting bugs fast, and boosting site speed without manual work.

https://github.com/ChromeDevTools/chrome-devtools-mcp