Trending AI repositories
Tracked daily across the agentic ecosystem. Velocity is computed from our own snapshot history — collecting the first week of data now; repos are linked to the startups behind them.
Autonomous software engineering fleet of AI agents for production-grade PRs on AgentField: plan, code, test, and ship.
More is Different. A multi-agent world engine where AI agents live, talk, compete, ally.
CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch. Works with Claude Code, Codex, Cursor, OpenCode, Kiro, and more.
Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.
Open-source local-first AI agent for desktop work. No account, no telemetry: use local models with Ollama/Rapid-MLX or bring your own provider key.
Healthy Diet AI Agent is a Bun + TypeScript backend for nutrition chat, food-image analysis, RAG document ingestion, and knowledge-grounded diet guidance.
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.
Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run
国内首个企业级 IT 运维多 Agent 自动化平台 — 基于大语言模型的智能运维解决方案。ITOps Agent Platform通过可视化工作流编排，将多个AI Agent组合成智能运维自动化流水线，实现服务器管理、告警处理、故障诊断、日志分析、脚本管理、定时运维任务的自动化执行， 支持国内外主流大模型，旨在 Zabbix/Prometheus 告警自动修复闭环，Docker 一键部署，多平台兼容。
Agentic Development skills behind the JS Mastery workflow
CLI for running large numbers of coding agents in parallel with git worktrees
Personal-Model First Self Evolving AI Agent 🐘
Spec-driven, agentic workflow framework for AI coding agents. Turn a request into a verifiable goal loop — plan, act, verify — with durable specs and evidence in your repo. Works with Claude Code, Codex, Gemini, OpenCode, and plain CLI.
The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data.
Run a task with AI as a flow of steps you keep, reuse, and refine, not a one-off chat.
Use agent to learn agent - A skeleton course on how to design, build, and operate production AI agents
🛠️ The meta-harness for AI agents — scaffold your own focused, branded agent harness with its own npx CLI, MCP server, memory, learning loop, and witness-signed releases. Works with Claude Code, Codex, pi.dev, Hermes, OpenClaw, and RVM (hardware-isolated sandbox).
Inference-native Tokenmaxxing Agent Harness for Loop Engineering
KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.
Event-sourced graph runtime for durable and stateful agents
Open-source runtime AI agent security tool - monitors and controls AI agents, catching malicious tool use, prompt injection, and policy drift in real time, before the agent acts.
This project is an AI Agent orchestration platform. It uses an LLM-driven decision engine, combined with capabilities (built-in tools, MCP protocol, CLI execution, browser operations, etc.), to achieve a basic closed loop from perception → planning → execution → feedback.本项目是一个面向 AI Agent 编排平台。它通过 LLM 驱动的决策引擎，结合能力（内置工具、MCP 协议、CLI 执行、浏览器操作等）
Curated list of LLM-driven trading agents, MCP servers, and agent skills for market research, strategy, and execution.
SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning
UI layer for the native Hermes orchestration features
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.
Governed shared memory for AI agent fleets — multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.
Official code for "Self-Distilled Agentic Reinforcement Learning"
面向硬件产品PCB方案设计的AI Agent，Agent会自动帮你进行需求确认，实时分析国内外各类芯片技术方案，进行器件选型，下载datasheet，输出BOM表，计算价格，输出模块原理图，最终整合成可落地技术方案。
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond