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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
The is a professional-grade Python implementation of the . It provides a structured environment for Large Language Models (LLMs) to interact with external tools and knowledge bases through a...
Index your documentation from across the sources and serve it via the Model Context Protocol (MCP) and REST API.
Learn how to implement MCP client with SwiftUI and Anthropic API
This implementation is based on the Model Context Protocol (MCP) put forward by Anthropic. For more information on MCP, please have a look at their official documentation.
A comprehensive collection of courses and tutorials for learning the - an open protocol that standardizes how AI applications connect to external tools and data sources.
Implementation of a model context protocol (MCP) client that connects to an MCP server using HTTP streamable (recommended) transport and displays the conversation in a chat-like UI.
The Visual Control Plane for MCP Servers & AI Skills.
Enterprise Governance Layer (Identity, RBAC, Credentials, Auditing, Logging, Tracing) for the Model Context Protocol SDK
A distributed runtime system for federated AI services with edge computing capabilities.
Trusted Model Context Protocol (Trusted MCP)
OmniMCP provides rich UI context and interaction capabilities to AI models through Model Context Protocol (MCP) and microsoft/OmniParser.
FastMCP for Google's langextract library
Agent Skills
This project is under active development and evolving rapidly. Contributions, feedback, and discussions are warmly welcome.
Agent skill that audits vibe-coded apps for common security vulnerabilities introduced by AI coding assistants
A high-performance Markdown parser and renderer for Angular, React, Svelte, Vue, HTML and ANSI.
A collection of Codex/agent skills for planning, documentation access, frontend development, and browser automation.
简单说，就是跟 Claude 说一句话，它会帮我从每天的新论文里筛一轮，挑出值得看的，再把重点论文读完、写成 Obsidian 笔记。日常不用记一堆命令，基本就是：