487 个 · 应用 · AI 核心
面向 Zed 的智能代码库搜索与索引。异步 MCP server，支持 LanceDB/BM25 混合搜索、多桶 RAG 以及自主 self-healing workflow。高性能、内存安全，可直接用于生产代码。Intelligent codebase search & indexing for Zed. Async MCP server featuring LanceDB/BM25 hybrid search, multi-bucket RAG, and autonomous self-healing workflows. High-performance, memory-safe, and ready for your production code.
语音 AI API 的开放价格数据库 —— STT、LLM、TTS、S2S、VAD。Open price database for voice AI APIs - STT, LLM, TTS, S2S, VAD
首个内置 MCP（server + client）的语言；Semantic Pipeline Runtime 提供 198 个内建函数、AI pipeline、沙箱化 Agent，单一二进制约 7 MB，零依赖。The first language with built-in MCP (server + client). Semantic Pipeline Runtime: 198 builtins, AI pipelines, sandboxed agents, single ~7 MB binary, zero dependencies.
Spec Seatbelt 让 AI 编程 Agent 保持诚实：先写计划、逐步证明、以全新视角验证；一次加载一个阶段（token 用量减少约 70%）；持久化的 .specs/ 记忆、循环计划波次与任务图，支持安全的并行工作。支持 Cursor 与 ClaudeSpec Seatbelt keeps AI coding agents honest: write the plan first, prove each step, verify with fresh eyes. Load one phase at a time (~70% fewer tokens). Persistent .specs/ memory, loop-plan waves, and task graphs for safe parallel work. Cursor & Claude.
使 AI agent 能够在任何市场上自主创建、评估与进化 Skill，无需用户干预Enable AI agents to autonomously create, evaluate, and evolve skills across any marketplace without user intervention.
本地优先的 AI 论文阅读助手 —— Agentic RAG、引文追溯、Electron 桌面应用，完全离线。Local-first AI reading assistant for academic papers — Agentic RAG, citation tracing, Electron desktop app, fully offline
🖥️ 通过终端中键盘优先的 Kanban board 简化工作流，实现快速、专注的任务管理。🖥️ Streamline your workflow with a keyboard-first Kanban board in your terminal for fast, focused task management.
使用 SQLite 和 FAISS 存储、整合与召回 coding agent 记忆，附带 provenance 追踪，实现快速、结构化的知识访问Store, consolidate, and recall coding agent memories with provenance tracking using SQLite and FAISS for fast, structured knowledge access.
Agents as Infrastructure。自托管多 Agent MCP server——具备 workspace、持久记忆与层级结构的长期运行 Agent。配备真实管理 UI、OAuth 2.1、静态加密 secrets。Agents as Infrastructure. Self-hosted multi-agent MCP server — long-lived agents with workspaces, persistent memory, and hierarchy. Real admin UI, OAuth 2.1, encrypted secrets at rest.
🌟 利用 GPU 加速 Apple Silicon 上的 SQLite 数据库操作，提升分析速度与数据管理效率🌟 Accelerate SQLite database operations on Apple Silicon with GPU power for faster analytics and efficient data management.
AI Agent 的认知操作系统——浏览器与计算机智能、持久化任务、记忆、恢复、证据与受治理的真实世界行动。A cognitive operating system for AI agents — browser & computer intelligence, persistent missions, memory, recovery, evidence, and governed real-world action.
基于 LlamaIndex、Redis 与 PII 脱敏的 RAG 搜索引擎。RAG search engine using LlamaIndex, Redis, and PII masking.
使用先进的 RAG 系统发现你的下一部心仪动画，提供精准推荐与增强语义搜索。🎬 Discover your next favorite anime with this advanced Retrieval-Augmented Generation system, offering precise recommendations and enriched semantic search.
面向 AI Agent 的低开销记忆后端 —— 单二进制，内存占用约 50MB，支持验证增强准确性Low-footprint memory backend for AI agents — single binary, ~50MB RAM, verify-augmented accuracy
Delta-9 MAW — 按严重程度（P0–P3）路由的多 Agent 异常处理流水线 + TOTP 操作面板，并配套线上 d9bkk.com 会员商店（KYC、D9-Wallet、PromptPay、TCG Lottery Pack）。Delta-9 MAW — severity-routed multi-agent anomaly pipeline (P0–P3) + TOTP operator panel, alongside the live d9bkk.com member storefront (KYC, D9-Wallet, PromptPay, TCG Lottery Pack).
Claude Code 的治理与可审计层：在 CEO 协议下运行由专业 Agent 组成的结构化团队——plan→debate→execute 门控、防篡改审计日志、跨 LLM 双重护栏。Governance & auditability layer for Claude Code: run a structured team of specialist agents under a CEO protocol — plan→debate→execute gating, tamper-evident audit log, cross-LLM pair-rail.
针对 AI Agent 的确定性审批、拒绝、取消、超时、重放及副作用安全测试 —— 无需 API key。Deterministic approval, rejection, cancellation, timeout, replay, and side-effect safety tests for AI agents—no API keys required.
为 AI agent 提供可验证的记忆：写入受控、读取带溯源、双时态历史、无法回答时选择 abstention 而非幻觉。AGPL/商业双重许可。Verified memory for AI agents: gated writes, provenance on every read, bi-temporal history, abstention instead of hallucination. AGPL/commercial.
Sago AI：数秒内从 Markdown 描述生成任意应用（2026）🚀 Sago AI: Generate Any App from a Markdown Description in Seconds (2026)
一个面向 PDF 文档问答的全栈 RAG 应用：上传 PDF，将其索引到本地向量库，然后基于页面级答案进行对话，并在内置阅读器中通过可点击引用跳转到对应页面。A full-stack retrieval-augmented generation (RAG) application for question answering over PDF documents. Upload a PDF, index it into a local vector store, then chat with page-grounded answers and clickable citations that jump to the right page in the built-in viewer.
专注后端的 fullstack 与 applied AI 开发。基于 LLMs 与 agents 构建有趣的项目，执着于 clean architecture 与零缺陷代码的生产部署。Backend-focused fullstack & applied ai dev. Building cool stuff with LLMs & agents. Obsessed with clean architecture & shipping no-bug code to prod.
Amadeus（来自《Steins;Gate 0》的 AI 助手）适配 DeepSeek Harness。Amadeus (AI assistant from Steins;Gate 0) for DeepSeek Harness
非官方的 MCP server，用于 AI 驱动的 NI Multisim 电路生成、仿真、数据导出与报告。Unofficial MCP server for AI-driven NI Multisim circuit generation, simulation, data export, and reports
使用 AI agent 自动化文献综述，基于结构化协议实现全面研究与高质量报告生成📚 Automate literature surveys with AI agents using a structured protocol for thorough research and insightful report generation.
AI 安全测试——发现 LLM 应用、聊天机器人、AI Agent、MCP 服务器与 RAG 系统中的安全漏洞。对齐 OWASP（LLM、Agentic、MCP）与 NIST AI RMFAI security testing — find security vulnerabilities in LLM apps, chatbots, AI agents, MCP servers, and RAG systems. Mapped to OWASP (LLM, Agentic, MCP) and NIST AI RMF.
插件化形态的 14-Agent 软件公司：在硬性预算上限内规划、构建并对每次变更进行对抗式评审。Markdown + POSIX shell，零运行时依赖。A 14-agent software company in a plugin: plan, build, and adversarially judge every change under hard budget caps. Markdown + POSIX shell, zero runtime deps.
面向可信 AI Agent 的开源基础设施，覆盖身份、权限、执行、证据、验证与 Agent 间组网。Open-source infrastructure for trusted AI agents — identity, permissions, execution, evidence, verification and agent-to-agent networking.
开放式数据库工程课程 · 14 个模块共 64 节课 · 210 小时 · 涵盖概念建模、分布式架构、运维及面向 AI 的数据恢复 · 109 项参考文献（带 ISBN、DOI 或标准号），逐课引用并在 CI 中校验 · 5 个零依赖可执行实验 · 256 题自测 📚🗄️ Programa abierto de ingeniería de bases de datos · 64 clases en 14 partes · 210 horas · Del modelado conceptual a la arquitectura distribuida, la operación y la recuperación para IA · 109 fuentes con ISBN, DOI o norma, citadas clase a clase y verificadas en CI · 5 laboratorios ejecutables sin dependencias · Autoevaluación de 256 preguntas 📚
基于 RAG 的文档问答机器人，可对任意 PDF/文本文件提问。使用本地 embeddings + Groq API。学习要点：embeddings、向量搜索、分块、RAG 流水线。Document Q&A bot using RAG (Retrieval-Augmented Generation). Ask questions about any PDF/text file. Uses local embeddings + Groq API. Learns: embeddings, vector search, chunking, RAG pipeline.
《大模型推理原理与优化》：面向系统/架构/后端研发工程师的模型原理入门课，目标是通俗易懂的解释推理过程，理解原理有助于系统开发/维护工作
2026 终极 AI Coding Agent 连续性工具包——无缝交接与同步。Ultimate AI Coding Agent Continuity Toolkit 2026 - Seamless Handoff & Sync
面向 Solana 上 AI Agent 的语义交易验证。Semantic transaction verification for AI agents on Solana.
官方 SELAT 插件——发现经过审核的 Skill 与联邦化 x402/MPP 能力，可通过你自己的 Circle Agent Wallet（自托管）从任意 Agent 支付。Official SELAT plugins — discover vetted skills and federated x402/MPP capabilities, pay from your own Circle Agent Wallet (self-custody), from any agent.
用于微调的合成数据样本集合，旨在为更大规模合成数据集提供种子数据This is a collection of synthetically generated datapoints for fine tuning meant for seeding larger synthetic datasets.