Cursor Руководство установки
AI-редактор кода, часто используемый с developer MCP.
MCP Servers
A Model Context Protocol (MCP) server that converts Mermaid diagrams to PNG images or SVG files. This server allows AI assistants and other applications to generate visual diagrams from textual...
curl https://cryptocurrency.cv/api/news • LLM Docs • Full API Docs • OpenAPI
- A Model Context Protocol (MCP) server with across 11 categories and from systematic CRAN task views.
For MCP users, lets LLM clients such as Cursor and Claude Code design Cisco-style networks directly through Model Context Protocol tool calls.
Fleet memory for AI agents — governed, shared, self-improving.
Semantic Code Retrieval for AI Agents — Hybrid Search • Graph Expansion • Token-Aware Packing
An open source Model Context Protocol (MCP) server and command-line tool that helps your AI coding assistants quickly create baseline IAM policies that you can refine as your application evolves, so...
MemoryMesh is a knowledge graph server designed for AI models, with a focus on text-based RPGs and interactive storytelling.
🍃🔎 MongoDB Lens: Full Featured MCP Server for MongoDB Databases
This is a Model Context Protocol (MCP) server for the Facebook Ads Library.
Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework for JupyterLab. It adds chat, inline edit, auto-complete, and an agent that can drive notebooks — backed by GitHub...
: This server only works on Windows operating systems due to its dependency on Windows-specific COM interfaces.
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：