Claude Desktop 설치 가이드
로컬 MCP 설정을 지원하는 데스크톱 클라이언트.
MCP Servers
Опубликовано на Infostart: https://infostart.ru/1c/tools/2720241/
A progressive AI Agent Harness tutorial written in Rust.
Installing MCPs is a huge pain, so I made a CLI tool to make it easier.
Knowledge graph + MCP tool server for LLM agents with hybrid retrieval, live DB sync, Korean FTS, and memory feedback.
A starting point for Claude Code to Codex collaboration
IDE-style navigation for structured data — code, JSON, YAML. Jump to definitions, find callers, follow references. Available as an MCP server or a mounted folder.
- — MCP Protocol v2 (spec revision 2026-07-28, streamable HTTP) and experimental StrongDM API support are here — see the release notes.
Local-first memory layer for CLI agents. Indexes Claude Code, Codex CLI, and Cursor session histories into SQLite + FTS5 — searchable from a CLI, TUI, or MCP server so your next agent session can...
Agent-managed GitHub merge queue for Codex, Claude Code, Cursor, and MCP clients
Self-hosted audit trail for AI agents — one command or one dashboard click from any step back to root cause.
Every local AI coding session in one tab: Claude Code, Codex and OpenCode in a single list, with a queue you can schedule and isolated Claude Desktop instances kept apart. Local, private, MCP-native.
Testing and evaluation platform to chat, inspect, and debug MCP servers, MCP apps, and ChatGPT apps.
Agent Skills
📄 bruce-doc-converter - Office/PDF 与 Markdown 双向转换，自动渲染 Mermaid 图表，让 AI 轻松读懂你的文档
dsh-agent-teams turns the current DeepSeek Harness session into a captain that can assemble durable sub-agents, split a goal into dependency-aware tasks, and coordinate work through direct messages.
Documentation • 中文文档 • Live Examples • Tutorials
所以做了这个可以蒸馏任意账号/作者写作风格的 agent skill，让写作不再痛苦，不再从 0 开始难产。
High-fidelity AI image prompt reverse-engineering skill for Codex
Agent skills for Railway, following the Agent Skills format.
Built by a physician-researcher, tested on real publications.
一行命令,让你的 AI 助手学会查文献、写综述、跑回归、管引文、写基金—— 科研龙虾 (Research-Claw) 的内置技能库,同时兼容 40+ 主流 Agent 框架。
- 简历精修（针对 AI / Agent 岗位优化） - 项目包装（这是最核心的，根据你过往的工作/实习和项目经历，定制化包装成agent项目，尽量多地融入agent主流技术，以及给你一份面试时口述的逐字稿） - 模拟面试（结合你的项目经历和大厂常问的问题进行深挖） - 全程陪跑（从投递到拿 offer）
다이소(제품/매장/재고), 상품 가격 비교, 주변 음식점/카페, 주유소/유가, 개발자 요청 제출, 롯데마트(매장/상품), GS25(매장/상품/재고), 세븐일레븐(상품/매장/재고/인기검색어/카탈로그), CU(매장/재고), 이마트24(매장/상품/재고), 올리브영(매장/재고), 메가박스(지점/영화/시간표/좌석), 롯데시네마(지점/영화/좌석),...
Bring your Entire context to your agents with cross-agent skills.
把一句「把这个流程做成 Skill」，变成一个真正能被发现、能稳定触发、能通过验证、还能一键开源的 Skill。