Claude Desktop Руководство установки
Десктопный клиент с поддержкой локальной конфигурации MCP.
MCP Servers
A Model Context Protocol server starter template
It lets MCP hosts — Claude Desktop, Claude Code, Cursor, VS Code — create, query, and modify OpenStudio models, run EnergyPlus, and read results, all in plain language.
Flagship Model Context Protocol server for generating Product Requirement Documents (PRDs) from codebase context.
MCP server for Minecraft Development
Model Context Protocol server for KiCad on Mac, Windows, and Linux
A Model Context Protocol (MCP) server that provides a standardized interface for AI assistants to interact with a SurrealDB database.
PubNub MCP Model Context Protocol Server for use in Cursor, Windsurf, Claude Desktop, Claude Code and OpenAI Codex and more!
Enterprise MCP server for SQL Server with 20 tools for schema discovery, data operations, and administration.
Asterisk Model Context Protocol (MCP) server.
Bioinformatic MCP server that wraps the most useful functions of the gget library
MCP server for AvaloniaUI
Model Context Protocol server for GraphQL
Agent Skills
llmdoc is a doc-driven workflow for both Claude Code and Codex.
SkillOps = Validate, manage, and deliver skills at scale.
Research-first Agent Skills for Deep Learning Experiments.
面向法律人的 Skills 集合。
Define instructions, skills, agents, MCP servers, hooks, workflows, and policies once. Compile native configuration for 49 AI coding platforms.
A structured development workflow for AI coding agents that brings , , and (only humans should) to AI-assisted development. TRIP helps you enter flow state and eat features like buttered noodles.
Official Convex plugins for AI coding agents, providing development tools for building reactive backends with TypeScript.
Fastest-growing GitHub repo ever - 9K to 195K stars in 66 days (18x faster than Kubernetes)
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前端 · 后端 · 移动端 · DevOps · AI 设计工具 — 生产级品质，独立安装。
This is a Python library that binds to Apache Arrow in-memory query engine DataFusion.
Elves is an open-source Agent Skill for handing planned development or research work to a separate worker without locking the run to one model provider.