Build and run agents you can see, understand and trust.
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Updated
Apr 8, 2026 - Python
Build and run agents you can see, understand and trust.
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
LLM-powered Agent Runtime with Dynamic DAG Planning & Concurrent Execution
fullstack chat agent with authentication, request credits and payments built in
Thoth - Personal AI Sovereignty. A local-first AI assistant with integrated tools, a personal knowledge graph, voice, vision, shell, browser automation, scheduled tasks, health tracking, and messaging channels. Run locally via Ollama or add opt-in cloud models. Your data stays on your machine.
🤖 MateClaw — Java + Vue 3 AI Assistant with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, and Multi-Channel Support. Built on Spring AI Alibaba.
The Karpathy treatment for OpenClaw - stripped to ε. 515 lines of Python, 6 files, one dependency.
The minimal AI agent engine
A complete LangGraph multi-agent system demo using SQL tools, Tavily search, MCP Toolbox, and OpenRouter models — with reproducible notebooks and a full supervisor-led agent workflow.
🤖 Advanced AI agent system combining ReAct reasoning and Plan-Execute strategies with unified memory, reflection patterns, and browser automation tools. Built with LangGraph, LangChain, and Google Gemini.
Lightweight Python SDK for LLMs with unified API across 9 providers. Built-in ReAct & Plan-Execute agents, streaming, native tool calling, context injection, structured outputs, and observability.
EdgeCrab 🦀 A Super Powerful Personal Assistant inspired by NousHermes and OpenClaw — Rust-native, blazing-fast terminal UI, ReAct tool loop, multi-provider LLM support, ACP protocol, gateway adapters, and built-in security hardening.
The self-hosted AI workstation. Autonomous screen agents, 3-tier neural routing, parallel agent swarms, video generation, 4K/8K upscaling, RAG, voice interface, 57-tool execution engine — all running locally on your hardware.
An AI-powered investment analysis tool 📈 that leverages simple ReAct AI agent flow framework and financial analysis techniques to provide comprehensive portfolio insights. This intelligent agent helps investors make data-driven decisions by offering deep portfolio risk assessment, stock profiling, and personalized recommendations.
A simple ReAct agent that has access to LlamaIndex docs and to the internet to provide you with insights on LlamaIndex itself.
Production-ready agent implementations: SimpleAgent, ReactAgent, MultiAgent, MemoryAgent, RAG variants, and more
Ship customer-facing AI with isolation, spend controls, and provenance.
JS bindings for Cross-Language MCP Orchestrator, think of LangChain + Vercel AI kit but for MCP
A practice repository implementing examples from the official LangChain documentation
Innovative AI agent implementations using LangGraph—featuring ReAct, RAG (Corrective, Self, Agentic), chatbots, microagents, and more, with multi-AI agent systems on the horizon! 🤖🚀
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