AI Agents & Frameworks
Autonomous agents and the frameworks to build them — orchestration, planning, multi-agent systems. Tracked daily with star velocity from real snapshots.
Federation over Text (FoT) is a federated-learning-like paradigm for multi-agent reasoning.
TAgent 是一个基于 Java 17、Spring Boot、Spring AI 和 DDD 分层构建的 AI Agent 工程实践项目。 它不是只封装一次模型调用，而是覆盖了一次 Agent 请求从接入、路由、运行时装配、规划执行、RAG、记忆、MCP 工具治理、人工审批、执行中干预，到 SSE 流式输出和全链路观测的完整过程。
Shared memory + orchestration for your coding agents — one MCP server, persistent vector memory, agent registry
An ongoing, collaborative meta-analysis about Human-AI-Interactions. We aggregate data and knowledge to build a non-abrasive, user-friendly prompting framework tailored to LLM mechanics, ensuring reasoning stability and a friction-free prompting environment that is safe for the human psyche and wellbeing.
Open-source AI-era employment platform connecting skills, jobs, enterprises, governance, and AI agents.
Open-source AI coding agent for the terminal. Claude Code-grade accuracy with smart model routing — uses the right AI model for each task, cutting costs 10x. Supports Claude, GPT, Gemini, DeepSeek & more.
The deterministic merge gate for AI-generated agent capability changes — a local-first, static Tool-Use Readiness review for MCP, OpenAPI, and SDK tool surfaces. Open-source CLI + GitHub Action.
Open-source control plane for Codex projects: Git-backed context, visible agent progress, scoped MCP access, resumable work, and safe handoffs.
200 production-grade DESIGN.md design systems for the world's best apps. Framework-neutral plus SwiftUI, Jetpack Compose, and Expo. Hand one to your AI agent, ship pixel-matched UI.
Copilot CLI skill that analyzes your repo and generates AI-ready configuration — AGENTS.md, copilot-instructions, skills, CI, issue templates, and more.
Kyros — The Memory OS for AI Agents Give your AI agents secure, self-correcting, persistent memory in 3 lines of code. Three memory types (episodic, semantic, procedural) with built-in forgetting curves, cryptographic integrity, and automatic contradiction resolution. Model-agnostic REST API with Python and TypeScript SDKs.
Turn your team's AI coding sessions, GitHub code, and docs into one shared, searchable memory — a self-hosted git truth store you query right from your editor over MCP.
GitHub as a knowledge graph for AI agents. Autonomous dev pipeline for Claude Code - investigate, build, review, merge. Issue in, PR out.
Automotive Agent Protocol
Automate viral reel/tik-tok videos via AI multi-agent system. ~$0.1/reel.
Local-first TUI for AI coding-agent session history: trace cost, tokens, time, tool failures, latency, health, diffs, reports, and CI gates across local agent logs.
🔎 深度研搜对话式多智能体 AI Agents，最适合系统学习 DeepAgents 的实战项目｜AI Deep Research Agent 实战 · LangGraph + RAGFlow + Tavily + FastAPI + WebSocket 从0到工程化落地。前后端完整代码全栈可跑，Docker 环境一键部署，配套 ai-agents-from-zero 免费教程与章节代码分支。适合系统学习大模型应用、多智能体 Agent 和企业级 AI 工程落地
Agent Harness Platform — shareable workspaces, MCP tools, skills, memory, and cron/webhook automations. Self-hosted and transparent.
Selfhost modern LLM stacks. Run the whole fleet from your terminal
Expert-thinking AGENTS.md profiles that teach AI agents to reason like senior scientists and engineers.
VS Code Extension for the Pi Agent.
Forge a working, testable, publishable MCP server in 30s. TypeScript or Python, with example tools, the Inspector and tests included.
Local-first AI learning workspace — ask, note, review and create around your own materials. Wiki KB, Agents, Skills, creation tools.AI 学习工作台，围绕你的资料完成问答、笔记、复习和创作输出。本地优先，多模型，Wiki 知识库，AI Agent，创作工具。
Dataflow-Oriented Reinforcement Learning for (Multi-)Agentic LLMs
Durable, file-based long-term memory for AI agents. Five-package plugin family: SDK, CLI, MCP server, Hermes adapter, and a LangGraph BaseStore. No vector database, no embeddings.
Edit Videos and Design Images with Claude code or Codex
Don't be the 40%. A production-ready blueprint for governing autonomous AI agents in IT operations — with executable policies, typed tool contracts, ISO 42001/NIST AI RMF mapping, and a 4-level maturity model. Vendor-neutral.
Stop re-explaining yourself
Build LangGraph agents like Next.js apps.
Fixing GRPO training collapse in long-horizon multi-tool agents. A lightweight PRM-Lite + LATA joint approach achieves +37% over vanilla GRPO on τ-bench airline (50-task, multi-turn).