270 个 · 框架
面向 Bun 的、强约定的全栈框架，主要用户是 AI Agent。八个原语，统一的 authz 系统覆盖所有入口，错误信息附带可直接执行的修复命令。可在 PaaS 上免费起步，扩容无需改动应用代码。Bun-only, opinionated full-stack framework where the primary user is an AI agent. Eight primitives, one authz system across every surface, errors that carry an exact fix command. Start free on a PaaS; scale out without changing app code.
面向银行内部产品审计的深度研究 LLM Agent + RAG 平台，提供带引用报告、PDF 导出与 pgvector 支持。Deep-research LLM agent + RAG platform for internal bank-product audit — cited reports, PDF export, pgvector
BMAD 的精简版本，对较小 AI 计划额度更友好。A slimmed-down version of BMAD made to be friendlier to smaller AI plan limits
AI Agent 集群的开源任务控制中心 —— 对话即可配置，Agent 负责执行，人类负责审批。Open-source mission control for AI agent fleets — chat to provision, agents to operate, humans to approve.
用于实时技术分析与市场执行的自主 agentic 框架。Autonomous agentic framework for real-time technical analysis and market execution.
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。
1,716 道 AI/ML 面试题（含答题框架）、69 张架构图、按角色的学习路径，以及语音驱动的模拟面试工具。覆盖 LLM、RAG、agent、MCP/A2A、系统设计、MLOps、安全与云部署。1,716 AI/ML interview questions with answer frameworks, 69 architecture diagrams, role-based study paths, and a voice-enabled mock interview simulator. Covers LLMs, RAG, agents, MCP/A2A, system design, MLOps, safety and cloud deployment.
Cortex System：AI 工程领域的操作系统，治愈技术健忘症。Cortex System: The Operating System for AI Engineering. Cure Technical Amnesia.
🤖 生产级 AI agent 编排平台，支持实时流式输出与多工具执行🤖 Orchestrate AI agents with ease using this production-ready platform, featuring real-time streaming and multi-tool execution capabilities.
基于 RAG、LangGraph 多 agent workflow、FastAPI 与 PostgreSQL（pgvector）构建的 AI 教育内容生成平台。生产级架构，集成 LangSmith tracing。AI-powered educational content generation platform using RAG, LangGraph multi-agent workflows, FastAPI, and PostgreSQL with pgvector. Production-ready architecture with LangSmith tracing.
自托管、100% 本地的 AI 平台——在一个 Docker 栈中集成 LLM 推理、RAG 与知识图谱。无需 API key。Self-hosted, 100% local AI platform — LLM inference, RAG, and knowledge graphs in one Docker stack. No API keys.
一切留痕：需求即 issue，决策即审批评论，工作即 PR，理由即该 PR 的记录。协调器将对话中继到 GitHub，并为每个角色派生沙盒化会话，各自仅持有自己的规则集。Everything on the record: a requirement is an issue, a decision is an approval comment, work is a PR, rationale is that PR's record. The orchestrator relays conversation to GitHub and spawns sandboxed role sessions, each with only its own rulebook.
🧠 构建模拟人类记忆的 AI 认知架构，分离情景记忆与语义记忆，并保证多语言支持与数据完整性🧠 Build a cognitive architecture for AI that mimics human memory, separating episodic and semantic memory while ensuring multilingual support and data integrity.
基于 Microsoft Agent Framework (.NET) 的 LLM Agent 三层评估：运行时护栏、PR 闸口、校准过的评审者。该框架可自我评估。Three-tier evaluation for LLM agents on Microsoft Agent Framework (.NET): runtime guardrails, a PR gate, and calibrated judges. The framework evaluates itself.
2026 年顶级开源 AI Agent 🤖 | 最佳自主工具与框架Top Open-Source AI Agents 2026 🤖 | Best Autonomous Tools & Frameworks
面向产品和 AI Agent 的自托管时序记忆平台。Self-hosted temporal memory platform for products and AI agents.
🛠️ 使用 Haystack 轻松构建强大搜索系统，该框架用于开发端到端问答与搜索应用。🛠️ Build powerful search systems effortlessly with Haystack, a framework for developing end-to-end question answering and search applications.
通过一次 wrap() 调用为 LLM 流水线构建运行时可靠性守卫，可配置地防御常见生产故障Build runtime reliability guards for LLM pipelines with one wrap() call and configurable protection against common production failures
Orchestra 的 AI 服务器——蓝图生成、任务分配、Clover 助手与知识图谱AI server for Orchestra- blueprint generation, task assignment, Clover assistant, and knowledge graph
WordPress 共享 AI 基础设施：provider 凭证、实时模型、提示词、标准化请求及 AI-Scribe 和兼容插件的使用记录。Shared AI infrastructure for WordPress: provider credentials, live models, prompts, normalised requests and usage records for AI-Scribe and compatible plugins.
自托管 Docker 栈，用于跨平台 AI Agent 工作区（Claude Code + ChatGPT + 任意 LLM）。MIT 许可。Self-hosted Docker stack for cross-platform AI agent rooms (Claude Code + ChatGPT + any LLM). MIT.
基于环境凭证的 CrewAI scaffold 与 Streamlit kickoff-client 学习。CrewAI scaffold and Streamlit kickoff-client study with environment-only credentials.
面向 AI 编程 agent 的平台无关工作编排，基于 MCP + CLI，提供跨提供商的统一面板（issues、scm、ci、deploy、notify）。Platform-agnostic work-orchestration for AI coding agents — one pane of glass (issues, scm, ci, deploy, notify) across providers, via MCP + CLI.
基于架构决策记录（ADR）理念的 Memory Framework，用于 AI agent（Claude Code、Codex、Antigravity……）之间的知识共享。支持 agent 安装，vector（Postgres + pgvector）+ graph（Neo4j）双骨干，通过本地 gateway 管理，支持多种本地 LLM 后端，具备完整 provenance、合并、遥测等能力。Memory Framework based on the idea of Architectural Decision Records, shared knowledge between AI agents (Claude Code, Codex, Antigravity ...). Agent installable, vector (Postgres + pgvector) + graph (Neo4j) backbone, managed through a local gateway, supporting multiple local LLM backends, with full provenance, consolidation, telemetry and more
开源的全流程演示文稿平台——构建、演示、发布与协作。自托管、原生支持 MCP、完全可定制主题。The open-source, end-to-end presentation platform - build, present, publish, and collaborate. Self-hosted, MCP-native, fully themeable.
本地优先、由 LLM 驱动的系统文献综述 (SLRs) 平台，以人机协同方式自动完成筛选与提取Local-first, LLM-powered platform for Systematic Literature Reviews (SLRs)—automating screening and extraction with human-in-the-loop precision.
本地优先的量化投资平台，支持可复现研究、证据约束决策、风险控制、论文/影子验证以及人工监督执行Local-first quantitative investing platform for reproducible research, evidence-bound decisions, risk controls, paper/shadow validation, and human-supervised execution.
Claude Code 学术写作框架：通过模式门控的 Agent 工作流，确保全文引用可核验、改写忠于原意、并保持作者风格Claude Code framework for academic writing: verified full-text citations, scope-faithful paraphrase, and voice preservation, enforced by a mode-gated agent workflow
Mistral Studio 产品营销策略、品类叙事、定位与信息框架、从专业消费者到企业的分层、销售作战卡、品牌资产与市场分析。Mistral Studio Product Marketing Strategy, Category Narrative, Positioning & Messaging Framework, Prosumer-to-Enterprise Segmentation, Sales Battlecards, Brand Assets & Market Analysis.
企业级数字支付平台：Java 21 / Spring Boot 3 微服务、Kafka 事件驱动、六边形（端口与适配器）架构，由专业 AI Agent 团队以 spec 驱动并编排，包含完整 CI/CD、GitOps 和供应链安全。Enterprise-grade digital payment platform: Java 21 / Spring Boot 3 microservices, Kafka event-driven, hexagonal (ports & adapters) architecture, spec-driven and orchestrated by a team of specialized AI agents. Includes full CI/CD, GitOps, and supply-chain security.
构建安全、有治理、可观测、成本可控的云与 AI 平台能力的实用参考框架。A practical reference framework for building secure, governed, observable, and cost-aware Cloud & AI platform capabilities.
基于 ESP32-P4（SeedSigner 生态）的无状态安全引导加载器分阶段开发，从文献综述起步，依次完成安全启动、SD 卡载荷加载、Specter bundle 验证以及反钓鱼加固。Phase-by-phase development of a stateless secure bootloader for ESP32-P4 (SeedSigner ecosystem) from literature review to secure boot, SD card payload loading, Specter bundle verification, and anti-phishing hardening
AI agents 的身份、记忆与协作平台——通过 CLI、MCP 和 Go 服务器提供事实、记忆、密钥管理及 agent 间消息传递。Identity, memory & collaboration platform for AI agents — facts, memories, secrets, and inter-agent messaging via a CLI, MCP, and a Go server.
项目一：竞赛团队——面向异质性乳腺癌的逻辑门控药物递送，竞赛撰稿进行中。项目二：两种蛋白之间的通用 RNA Linker，融合蛋白质粒进入第二轮设计迭代。项目三：基于 RNA 核糖开关的金属检测，启动全细胞生物传感的文献综述。Project 1: Competition Team - Logic-gated Drug Delivery for Heterogeneous Breast Cancer Competition Writeups underway Project 2: Generic RNA Linker between two proteins Plasmids for fusion proteins are in second round of design iterations Project 3: Metal Detection using RNA Riboswitch Beginning Literature Review for whole cell bio-sensing
在消费级 GPU 上自动化机器学习模型从论文阅读到实验执行与同行评审的完整研究工作流Automate the full research workflow from paper reading to experiment execution and peer-review for machine learning models on consumer GPUs.