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開発者向け MCP サーバーとよく使われる AI コードエディタ。
MCP Servers
A remote Model Context Protocol (MCP) server for interacting with the dev.to public API without requiring authentication.
A lightweight CLI tool to easily configure and initialize MCPs for Claude Code.
Turbular is an open-source Model Context Protocol (MCP) server that enables seamless database connectivity for Language Models (LLMs).
This Streamlit application provides a user interface for connecting to MCP (Model Context Protocol) servers and interacting with them using different LLM providers (OpenAI, Anthropic, Google, Ollama).
A Model Context Protocol (MCP) server for Apache Dolphinscheduler. This provides access to your Apache Dolphinshcheduler RESTful API V1 instance and the surrounding ecosystem.
An MCP server for workflowy
An MCP server for OSV
MCP server for LibreNMS management
This project demonstrates how to build interactive MCP (Model Context Protocol) widgets that run on Cloudflare Workers and can be embedded in AI chat interfaces like ChatGPT.
This project implements a small team of coding agents using LangGraph and the Model Context Protocol (MCP). The agents use MCP servers to provide tools and capabilities through a unified gateway.
This repository provides example implementations of MCP (Model Context Protocol) in Python and Typescript, based on the specification: 📄 MCP Streamable HTTP Spec.
Paper | Features | Installation | Usage | CLI | Development
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!