Cursor 安装指南
常与开发类 MCP Server 搭配使用的 AI 代码编辑器。
MCP Servers
Run Model Context Protocol (MCP) servers in the browser - no local setup required!
Expose llms-txt to IDEs for development
Model Context Protocol (MCP) server that gives LLM agents and chatbots direct access to the World Bank's Data360 Platform.
A Go adapter that bridges LangChain Go tools with Model Context Protocol (MCP) servers.
Generate an MCP for any web app
A lightweight MCP server that encapsulates the Exa Pool API as a toolkit for AI assistants to call.
Publish MATLAB functions as MCP tools for AI agents using MATLAB Production Server
This project shows how to implement an MCP (Model Context Protocol) server of Apache ECharts.
A Server-Sent Events (SSE) implementation using FastAPI framework with Model Context Protocol (MCP) integration.
Welcome to project! In this repository, you'll find multiple examples of setting up MCP Servers. MCP (Model Context Protocol) is a framework for AI models that enables them to store data, run tools,...
An MCP (Model Context Protocol) server that provides comprehensive RAG (Retrieval-Augmented Generation) capabilities for processing and querying directories of documents using the raganything library...
MCP server for fetch web page content using Playwright headless browser.
Agent Skills
Shiny for Python is the best way to build fast, beautiful web applications in Python. You can build quickly with Shiny and create simple interactive visualizations and prototype applications in an...
One Python API: store media, run models, index embeddings, serve endpoints, and version everything in a single system instead of gluing together blob storage, a vector DB, an orchestrator, and edge...
Adala is an **utonomous **ta (**abeling) **gent framework.
Beautiful UI components built for Better Auth.
KAI Scheduler is a robust, efficient, and scalable Kubernetes scheduler that optimizes GPU resource allocation for AI and machine learning workloads.
Your AI skills and agents, finally organized.
Model export recipes, Python primitives, and Swift runtime utilities for building on-device AI with Core AI.
本项目是基于吴恩达老师在 DeepLearning.AI 平台推出的 agent-skills-with-anthropic 系列课程的中文学习资料整理项目。我们致力于为中文学习者提供高质量的课程内容翻译、系统的知识点梳理以及详细的示例代码解读，帮助大家更轻松地掌握 Agent Skills。
A collection of AI agent skills focused on resume optimization, job applications, and career development.
For more advanced capabilities and end-to-end machine learning, visit www.k-dense.ai.
upfetch is an advanced fetch client builder with standard schema validation, automatic response parsing, smart defaults and more.
📚 Check out the comprehensive docs with detailed guides, examples, and best practices!