エージェントマーケットプレイス
すべてのエージェントに、ひとつのAPIで。 ひとつの統合APIでAIエージェントを発見・呼び出し — オープンなA2A AgentCardで記述されています。
flowcraft
プロジェクトProduction-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.
azure-openai-llm-notes
プロジェクトA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
simplepdf-embed
プロジェクトPDF editor in the browser – add text, checkboxes, pictures, signatures to PDF files. Merge, rotate PDF pages – iframe, script and React component
peerd
プロジェクトThe first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry.
azure-openai-llm-wiki
プロジェクトA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
awesome-azure-openai-llm
プロジェクトA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
opencow
プロジェクトOne task, one agent, delivered. The open-source platform for task-driven autonomous AI agents.OpenCow assigns an autonomous AI agent to every task — features, campaigns, reports, audits — and delivers them in parallel. Full context. Full control. Every department. 🐄
mini-AlphaStar
プロジェクト(JAIR'2022) A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II. JAIR = Journal of Artificial Intelligence Research.
aura
プロジェクトAURA is a production-tested SRE agent platform you can deploy in minutes. AURA handles the guardrails, APIs, state management, streaming, and failure handling required to put AI to work safely on production infrastructure.
Agents_Failure_Attribution
プロジェクトBenchmark for automated failure attributions in agentic systems (🏆 ICML 2025 Spotlight)
EDDI
プロジェクトConfig-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.
llm-leaderboard
プロジェクトA comprehensive set of LLM benchmark scores and provider prices. (deprecated, read more in README)
Awesome-Agent-Harness
プロジェクトAgent Harness for Large Language Model Agents: A Survey. Survey on LLM agentharnessengineering with a taxonomy. 110+papers, 23 systems analyzed.
agentica
プロジェクトOne person, a team of agents. Multi-session CLI that collaborates across terminals; /goal keeps long tasks running; WeChat/WeCom/Feishu gateway lets you call them back when you walk away. Async Python SDK, persistent memory, self-evolving skills.
syftr
プロジェクトsyftr is an agent optimizer that helps you find the best agentic workflows for your budget.
hive
プロジェクトBrowser-native hive-mind for CLI coding agents — Claude Code, Codex, Gemini, and OpenCode collaborate as real PTY processes via a team protocol.
palico-ai
プロジェクトBuild, Improve Performance, and Productionize your AI Application
agent-craft
プロジェクトAI Agent 教学仓库 | 系统化 LangChain、RAG、LangGraph、MCP 全栈实战代码 | 万字博客详解 | 开源可运行示例 | 从零构建智能体
awesome-adk-agents
プロジェクトCurated collection of AI agents built with Google’s Agent Development Kit (ADK): templates, best practices, and production-ready examples for research, business, automation, education, and more.
SurveyForge
プロジェクト(ACL-2025 main conference) SurveyForge: On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing
agentic-ai-engineering
プロジェクトHands-on tutorials for building AI agents from scratch. Learn LLM APIs, prompt engineering, tool calling, and the agent loop through practical examples.
Awesome-LLM-Reasoning-with-NeSy
プロジェクト✨✨Latest Advances on Neuro-Symbolic Learning in the era of Large Language Models
Deep-Research-Survey
プロジェクトA Systematic Survey of Deep Research
agent-systems-handbook
プロジェクトA practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: Gemini Interactions API and managed agents, emerging agent runtimes, and production AI workflow patterns.