Cursor Руководство установки
AI-редактор кода, часто используемый с developer MCP.
MCP Servers

A switchboard for AI in your browser: wire in any model, script WebMCP tools, connect remote MCP servers, bring your commands.

— Build structures through natural-language conversations with Claude.

Illustrative estimates. The ~90% is Claude-side token reduction on analysis-heavy tasks — not total cost: Kimi's own subscription still applies.

Use DeepSeek from Claude Code, Codex, or any MCP-compatible client as a small, cheap supervised worker.

Reqable MCP Server is a Dart-based MCP server that communicates with AI tools over stdio and exposes Reqable capabilities through MCP tools.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

MCP server for the Loreto skill generation API

— DSGVO, BFSG Barrierefreiheit und Einwilligungs-Widerruf. Auf Basis echter Gesetzestexte via rechtsinformationen.bund.de MCP.

mcp server for rust code semantic hybrid search bm25 + embeddings with tree-sitter, gpu accelerated indexing and merkle tree updates

AI-Powered Civil 3D Modeling

ACI indexes your code with embeddings and Tree-sitter AST parsing, then lets you search it with natural language. Results come back with exact file paths and line numbers, not just fuzzy matches.

Using ffmpeg command line to achieve an mcp server, can be very convenient, through the dialogue to achieve the local video search, tailoring, stitching, playback and other functions
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: