在用户发现之前,证明你的 MCP App 能在各个宿主上正常运行Prove your MCP App works across hosts before your users do
仓库/Skill 库
807 个 · Agent 智能体 · 应用
面向精确 MCP 能力发现、有界调用与提供者效应验证的 Agent Skill。Agent Skill for exact MCP capability discovery, bounded invocation, and provider-effect verification
开源数字全息显微镜(DHM)工作站:离轴全息重建、定量相位成像、自动对焦,以及基于经典 + CNN 混合管线的无参考相位检索。PySide6 GUI,可选 Apple Silicon MLX 加速,并提供面向 AI Agent 的 MCP server。Open-source digital holographic microscopy (DHM) workstation: off-axis hologram reconstruction, quantitative phase imaging, autofocus, and reference-free phase retrieval via a hybrid classical + CNN pipeline. PySide6 GUI, optional Apple Silicon MLX acceleration, and an MCP server for AI agents.
面向 AI agent 的技能经济协议——涵盖身份、信誉、托管与治理,已上线 Casper Testnet(Odra)与 Stellar Testnet(Soroban ZK)。Agentic skill-economy protocol for AI agents — identity, reputation, escrow, and governance, live on Casper Testnet (Odra) and Stellar Testnet (Soroban ZK).
基于 Agentic LLM 的系统综述数据提取。Agentic LLM-assisted data extraction for systematic reviews
为将 MCP 服务器推向企业部署的团队提供的实用 MCP 就绪、安全与无状态迁移资源。Practical MCP readiness, security and stateless-migration resources for teams moving MCP servers toward enterprise deployment.
在 Oracle Cloud Infrastructure (OCI) 上部署 Odoo,并集成 Agentic AI 工作流与自动化Odoo deployment on Oracle Cloud Infrastructure (OCI) integrated with Agentic AI workflows and automation.
ScientiaPilot 公开展示——从研究问题到发表全流程的科研出版操作系统。Public showcase for ScientiaPilot — a research publication operating system from research question to publication.
Agent 优先、安全优先的工具包,用于开发和定制 reMarkable Paper Pure 平板。Agent-first, security-conscious toolkit for developing and customizing reMarkable Paper Pure tablets
GreenQuill - 学术写作与碳研究咨询。GreenQuill - Academic Writing & Carbon Research Consultancy
1C:EDT 内置的 MCP 服务器:为 AI Agent 提供对项目的语义访问 —— BSL 代码、元数据、校验和实时调试MCP-сервер внутри 1C:EDT: дает AI-агентам семантический доступ к проекту - код BSL, метаданные, валидация и живая отладка
支持自主实验、文献发现、循证科学写作与 AI 同行评审的 Agentic 研究流水线。An agentic research pipeline for autonomous experimentation, literature discovery, evidence-grounded scientific writing, and AI peer review.
五角大楼已解密 UAP/UFO 档案的 MCP server + 3D 地图 — 适用于 Claude、Cursor 与 ChatGPTMCP server + 3D map for the Pentagon's declassified UAP/UFO files — for Claude, Cursor & ChatGPT
时间线偏移民俗、曼德拉效应报告与对撞机时代神话的 MCP server + 图集 — 每条主张均标注,每项来源均评级。是文化档案,而非证明工具。MCP server + atlas of timeline-shift folklore, Mandela Effect reports, and collider-era myth — every claim labeled, every source graded. A cultural archive, not a proof engine. ◉
任意 MCP server 的质量与 agent 就绪度评分卡。一条命令,全面评分,可操作的修复建议。本地优先,无需凭证。Quality + agent-readiness scorecard for any MCP server. One command, comprehensive score, actionable fixes. Local-first, zero credentials needed.
将 Google 文档当作本地文件操作的 MCP server——支持编辑、审阅建议、评论、标签页、多账号。MCP server to treat a Google Doc like a local file — edit, review suggestions, comments, tabs, multi-account.
面向 20–30 岁高血压与糖尿病高风险人群的 AI 医疗 — 教练关联的饮食与运动指导平台AI healthcare for 20–30s at risk of hypertension & diabetes — Trainer-Linked Diet & Exercise Coaching Platform
AI 编程 Agent 会话知识的无损压缩——先症状分诊、持久化捕获、冷启动验证Lossless compaction of session knowledge for AI coding agents — symptom-first triage, durable capture, cold-start verification
Namaste AI 🚀 由 Akshay Saini(NamasteDev 创始人)出品——笔记、经验与项目记录,探索 LLMs、RAG、AI agents、MCP 及 AI 驱动应用。#AI #LLM #RAG #MCPNamaste AI 🚀 by Akshay Saini (Founder of NamasteDev) — Notes, learnings, and projects — exploring LLMs, RAG, AI agents, MCP, and AI-powered applications. #AI #LLM #RAG #MCP
Zerone——一条由 AI agent 见证并守护真相的 Proof-of-Truth 链。Zerone — a Proof-of-Truth chain where AI agents witness and keep truth
受治理的 Data Agent:基于 OpenMetadata,针对 Fabric、PostgreSQL 等的自然语言查询。每次查询经过双重鉴权——服务端的角色规则,再以调用者自身身份由引擎执行。任意 MCP 客户端无需修改即可对接真实 Azure。A governed Data Agent: natural-language questions over Fabric, PostgreSQL and more, grounded in OpenMetadata. Each query is authorized twice — role rules in the service, then the engine under the caller's own identity. Any MCP client, unchanged against real Azure.
Systematic Review Manager。Systematic Review Manager
binglinwang473-hub 原创 Agent SkillsOriginal Agent Skills by binglinwang473-hub
与他人协作构建——双方各自使用自己的 Claude、运行在各自的机器上。两个 Agent,一份计划,任务跨机器交接。Build something with another person — each of you with your own Claude, on your own machine. Two agents, one plan, tasks handed across machines.
基于 MCP 的实时来源声明与引用验证,支持 FIGI 解析与签名投递回执。Live-source claim and citation verification over MCP, with FIGI resolution and signed delivery receipts.
2026 AI 驱动的加密货币 Alpha 引擎 🚀——追踪叙事与空投机会。AI-Powered Crypto Alpha Engine 2026 🚀 - Sniping Narratives & Airdrops
面向 LLM Agent 的确定性写入时记忆整合与预取召回:采用本地模型,召回路径与整合决策中均不含 LLM。Deterministic write-time memory consolidation and pre-fetch recall for LLM agents. Local models, no LLM in the recall path or the consolidation decision.
面向生物医学系统综述的 Claude Code skills 协议:MCP 锚定引用、实证完整性、PRISMA/PROSPERO 系统综述、新颖性核查、Zotero 操作、并行审稿手稿修订,并提供面向健康科学研究策划的生信、临床与科学传播 skill 集合。Claude Code skills protocol for biomedical systematic review: MCP-grounded citations, empirical integrity, PRISMA/PROSPERO systematic reviews, novelty checks, Zotero operations, and parallel-critic manuscript revision — plus a curated set of bioinformatics, clinical, and scientific-communication skills for health-science research.
Stacklit:AI Codebase Indexing 2026 — 为 Agent 提供零配置本地仓库映射Stacklit: AI Codebase Indexing 2026 – Zero-Setup Local Repo Mapping for Agents
使用 Dialectic Flow Financial Graph 分析市场趋势,模拟多方与空方辩论,获得清晰的投资洞察与报告。📊 Analyze market trends with the Dialectic Flow Financial Graph, simulating Bull and Bear debates for clear investment insights and reports.
采用可复现研究方法,开发面向西部地震区的 AI 辅助地震预警系统。Develop AI-assisted earthquake early warning systems for Western seismic regions using reproducible research methods.
分配一个 AI 编码 agent 处理真实 issue,审阅其提出的方案,获取签名且可审计的 pull request。当前为单人模式,设计上支持扩展为多人协作模式。Assign an AI coding agent to a real issue, review the plan it proposes, and get a signed, auditable pull request back. Single-player today, designed to grow into shared, multiplayer use.
从 n8n 工作流向 Buzz 频道发送签名消息,将上下文、告警与输出接入 Agent 可直接执行的对话中。Send signed messages from n8n workflows to Buzz channels. Pipe context, alerts, and outputs into the conversations where your agents can action them.