1428 个 · Agent 智能体
为 AI agent 提供持久化、结构化记忆。基于 Go 的本地优先 MCP server：语义召回、去重、provenance、冲突解决。单一静态二进制，零依赖。Persistent, structured memory for AI agents. Local-first MCP server in Go: semantic recall, dedupe, provenance, conflict resolution. One static binary, zero dependencies.
多租户 SaaS 自动化平台，具备事件驱动工作流、AI 驱动的文档处理与实时集成。Multi-tenant SaaS automation platform with event-driven workflows, AI-powered document processing, and real-time integrations.
SAM 的纯文档概述。SAM 是一个由 9 个 agent 组成的 LLM pipeline，用于自动化系统综述与 meta 分析。实现位于私有仓库。Documentation-only overview of SAM, a 9-agent LLM pipeline that automates systematic reviews and meta-analyses. Implementation lives in a private repository.
立场论文：编码 Agent 需要对代码库决策的显式建模，而不仅仅是结构建模。Position paper: coding agents need an explicit model of codebase decisions, not just structure"
将任何内容转化为 token 优化、布局感知的 Markdown，并精确知道为你节省了多少。无损压缩、诚实的 token 报告，CLI + MCP 服务器 + agent skill。Turn anything into token-optimized, layout-aware Markdown - and know exactly what it saved you. Lossless compression, honest token reports, CLI + MCP server + agent skill.
自托管共享记忆，面向 AI Agent 团队。支持房间（Rooms）、L0-L3 层级深度与 MCP；读取路径不调用任何语言模型。基于 vectorize-io/hindsight（MIT）的 fork。Self-hosted shared memory for a team of AI agents. Rooms, hierarchical L0-L3 depth, MCP. The read path never invokes a language model. Fork of vectorize-io/hindsight (MIT).
Conversational academic writing Copilot: LangGraph ReAct agent with citation tracing, faithfulness reviewer, RAG & Reflexion LaTeX self-repair ｜ 对话式学术写作 Copilot：LangGraph ReAct 智能体，引用溯源 + 忠实度审校 + RAG 检索 + Reflexion 编译自修复，端到端产出真实 PDF
一个开源的 Agentic 开发环境：在终端网格中并行运行 Claude Code、cursor-agent、Codex 与 shell，配合用于任务分派的看板、共享 Agent 记忆以及多 Agent 编排能力。An open-source agentic development environment: run Claude Code, cursor-agent, Codex and shells side by side in a terminal grid, with a kanban board that dispatches them, shared agent memory, and multi-agent orchestration.
用于生物学研究问题的科学研究 Agent。Scientific Research Agent for biological research questions
3D 记忆岛屿，让 Google ADK agent 将你的记忆保存为有据可查的书：基于 Gemini on Vertex AI、Firestore、Pub/Sub 的 dreaming 机制构建知识图谱与 dark keepers，配合 Cloud TTS/STT 语音。All Things Agentic Hackathon 参赛作品。3D memory island where Google ADK agents keep your memories as grounded books: Gemini on Vertex AI, Firestore, Pub/Sub dreaming that builds a knowledge graph and dark keepers, Cloud TTS/STT voice. All Things Agentic Hackathon entry.
基于证据的构建流水线，编排 10 个 AI 子 Agent，并通过确定性 5 道关卡验证系统证明正确性。Evidence-based build pipeline that orchestrates 10 AI sub-agents and proves correctness through a deterministic 5-gate verification system.
AI 驱动的每周生活规划器 — 由多供应商 Agent 生成饮食、学习、锻炼、习惯和娱乐方案，并附带每周日程追踪。AI-powered weekly life planner - nutrition, study, workouts, habits and fun generated by a multi-provider agent, with a weekly schedule tracker.
基于 Next.js、FastAPI 和 Supabase 的 AI 辅导应用。上传 PDF 与 URL，即可生成结构化摘要、多轮对话和自定义测验。自定义主题通过 Wikipedia、ArXiv 和 DuckDuckGo 进行联网搜索，以生成测验并围绕主题展开对话。Next.js AI tutor with FastAPI and Supabase. Upload PDFs and URLs to generate structured summaries, multi-session chat, and custom quizzes. Custom topics use web search through Wikipedia, ArXiv, and DuckDuckGo to generate quizzes and chat about the topic.
在 VS Code 中构建 AI 辅助的科研工作流：文献综述、引用追踪与可发表级导出Build AI-assisted scientific research in VS Code with literature review, citation tracking, and publication-ready export
面向 LLM agent 的 MCP server，用于加拿大调整后成本基础（ACB）与资本利得：支持平均成本法与 superficial-loss 检测。MCP server for Canadian adjusted cost base (ACB) and capital gains: average-cost, superficial-loss detection, for LLM agents.
NEXORA 的黑客松团队仓库 - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:nexora]Hackathon team repository for NEXORA - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:nexora]
Codiacs 黑客松团队仓库 - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:codiacs]Hackathon team repository for Codiacs - [hackindia-team:ai-first-startup-hackathon-build-a-startup-using-ai-only:codiacs]
Local-first 可视化任务图，使人类与 AI Agent 在目标、进度、推理与下一步行动上保持对齐。Local-first visual task graph that keeps humans and AI agents aligned on goals, progress, reasoning, and the next action.
隐私优先的本地 Web 研究 MCP server，集成 SearXNG、隔离 Tor 路径、证据抽取、排序与精确引用。Privacy-first local web research MCP server with SearXNG, isolated Tor paths, evidence extraction, ranking, and exact citations.
一个真实场景下的多能力 AI Agent，可接收用户的研究问题，自主决策所需信息，调用工具/MCP，分析信息并产出结构化报告。A real world multi capability AI agent that can take a user's research question, decide what it needs, use tools/MCP, analyze information, and produce a structured report.
GoVail MCP —— 用于 GoVail 平台集成的 Model Context Protocol server 与工具。GoVail MCP — GoVail 플랫폼 연동을 위한 Model Context Protocol 서버 및 도구
在真实 MCP 客户端上对 Remote MCP 服务器进行实时互操作性测试。Live interoperability testing for Remote MCP servers across real MCP clients.
本地优先的研究论文工作空间与可视化 AI Agent 工作流构建器Local-first research paper workspace and visual AI agent workflow builder
面向 AI Agent 调试 Android React Native/Expo 应用的本地运行时可观测性桥接层——以证据为先：截图、UI 树、逐请求网络数据、FPS、React 渲染、CDP console/heap/profile、确定性诊断、前后对比。Local runtime observability bridge for AI agents debugging React Native/Expo apps on Android — evidence-first: screenshots, UI trees, per-request network, FPS, React renders, CDP console/heap/profile, deterministic diagnosis, before/after compare.
本地优先的 CLI，用于评估 MCP server 的开销与能力，数据不离开本机。A local-first CLI that measures what an MCP server costs and what it can do. Nothing leaves your machine.
探索用于测试 ML、LLM 和 Agentic AI 系统的 AI 安全工具、论文与框架Explore AI security tools, papers, and frameworks for testing ML, LLM, and agentic AI systems
为 AI agent 搭建团队知识仓库——集中领域知识、工作流与规范，供 agent 消费、基于其开发，并通过 PR 循环持续保鲜。Scaffold team knowledge repos for AI agents — centralize domain knowledge, workflows, and specs that agents can consume, develop with, and keep fresh via PR loops.
Mielepiù 工程案例研究——一款 B2B 销售平台，其 AI Agent 基于真实数据作答并给出引用来源。Engineering case study of Mielepiù, a B2B sales platform whose AI agent answers on real data and cites its sources.
Athleta 工程案例研究——一款 AI 健身产品，采用每用户一个知识图谱的设计，由 Agent 提议、用户确认。Engineering case study of Athleta, an AI fitness product with a per-user knowledge graph where the agent proposes and the user confirms.
面向 AI Agent 的学术研究情报——论文检索、科学文献、引用分析、arXiv、作者指标、前沿研究与语义相关工作（pgvector）。支持 MCP + x402。Academic research intelligence for AI agents — paper search, scientific literature, citation analysis, arXiv, author metrics, trending research & semantic related-work (pgvector). MCP + x402.
基于 Hermes 的原生 AI 工作台，通过专业 Agent 与 Skill 完成经人工审核的精炼工作。A Hermes-native AI workshop for crafted, human-approved work through specialist agents and skills.