The universal open database and semantic vector search engine for AI Agent Skills, MCP Servers, Project Directives, and Rules. 3.48M+ assets across 7 ecosystems.
Local-first Agentic AI Infrastructure Platform with LLM Gateway, Agent DAG Runtime, MCP Tool Hub, A2A Agent Mesh, Local RAG, Tool Sandbox and Observability.
A unified AI agent system integrating Retrieval-Augmented Generation (RAG), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP) for document processing, web search, and intelligent task delegation.
READ-MAS generates software requirements specifications (SRS) and system designs from natural language queries using multi-agent AI orchestration built on Google ADK.
Interactive roadmap for becoming an Agentic AI Engineer — 11 stages from Python & FastAPI to multi-agent systems, MCP, RAG, Docker, and context engineering
Local-first multi-agent platform for financial research and trading. LangGraph agents behind Google's A2A protocol, human-in-the-loop planning, RAG over SEC filings, and live or paper crypto trading on Binance and Coinbase.
Comprehensive collection of AI concepts, research findings, and practical implementations. From machine learning fundamentals to cutting-edge LLMs, agents, and emerging technologies.