Open highlighted repo slot
Put your repository first
Promote a GitHub repo at the top of Awesome repository list views for 7 days.
GitHub projects from awesome lists
Search names, descriptions, topics, tags, and stacks, then tune results by ecosystem, freshness, health, and cross-list signal.
Open highlighted repo slot
Promote a GitHub repo at the top of Awesome repository list views for 7 days.
TypeScript AI platform with AI chat, Autonomous agents, Software developer agents, chatbots and more
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
Open-source, self-hosted Claude Code - a terminal AI assistant and the Python framework behind it. Tool-calling, sandboxed execution, multi-agent teams, skills, checkpoints, unlimited context - on Pydantic AI, any model.
Build agents which are controlled by LLMs
An LLM-powered repository agent designed to assist developers and teams in generating documentation and understanding repositories quickly.
Autonomous GPT-4 agent platform
A codebase wiki for AI coding agents. Captures what the code can't say: decisions, flows, invariants, gotchas.
An autoagentic AGI that is self-evolving and modular.
Open-source self-improving QA agent for software teams. A test harness with memory. Write tests in natural language for web and mobile. agent-qa learns from every run, adapts to UI changes, and catches regressions before you ship.
CUGA is an open-source generalist agent harness for the enterprise, supporting complex task execution on web and APIs, OpenAPI/MCP integrations, composable architecture, reasoning modes, and policy-aware features.
Your Company Agentic Operating System
data-to-paper: Backward-traceable AI-driven scientific research
Self-improving Agents
Hierarchical agent loops with recursive self-organization.
SkyAGI: Emerging human-behavior simulation capability in LLM
The most autonomous AI agent framework: runs unattended on GitHub Actions, self-healing skills, drives Claude Code, Grok, Codex & more. No approval loops. Configure once, forget forever.
Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.
An agent-native web security workspace. Find vulnerabilities through red-teaming. Formally verify properties of Rust codes in Lean 4.
Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude, GPT, Gemini, OpenRouter, Ollama). A practical Claude Code and LangChain alternative.
The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output. Works also with models not fine-tuned to JSON output and function calls.
Build agent that uses 80% less token and delivers better results.
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.
Let AI agents message, watch, and spawn each other across terminals. Claude Code, Codex, Antigravity CLI, Cursor CLI, OpenCode, Kilo, Pi, Kimi
Make your meetings accessible to AI Agents
The fastest developer workflow for every AI coding agent. Live status, quick prompts, worktrees, and diff review from one tmux TUI.
Giselle: AI App Builder. Open Source.
Open-source control plane for AI coding agents. Run an AI engineering team: parallel Claude Code, Codex, and Gemini workers with a shared board, atomic tasks, schedules, loops, origin-stamped messaging, model switching, and self-healing recovery. One dashboard, or your phone. MIT, single Rust binary.
🕵️♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.