LangGraph

Official A2A python sample agent: Langgraph

Build Agentic AI solutions on AWS, using latest OSS Agentic Frameworks.

NL2SQL - Ask questions in plain English, get SQL queries and results. Powered by LangGraph.

A production-ready agent server built with LangGraph that implements the Agent-to-Agent (A2A) protocol

Innovative AI agent implementations using LangGraph—featuring ReAct, RAG (Corrective, Self, Agentic), chatbots, microagents, and more, with multi-AI agent systems on the horizon! 🤖🚀

This repository features a collection of agentic AI projects across various domains, showcasing practical applications of AI agents with different frameworks, techniques, and tools.

Multi-agent research system in a node-based architecture represented in a cyclic graph, made with LangGraph, Gemini, FastAPI & React Vite.

Agent-to-Agent Protocol Specification — agent:// URI scheme for AI agent identity and discovery

Notes on gen AI concepts and tools. POC on agentic AI with MCP, A2A, langGraph, langchain, openAI LLM, crewAI

An agentic AI assistant, that is helping users with math queries to solve and explain them to the user.

Automated daily news generator using LLMs and vendor search, with date-organized, source-backed articles.

A distributed multi-agent system that orchestrates complex tasks across specialized AI agents using A2A (Agent-to-Agent) protocol, MCP (Model Context Protocol) and LangGraph.

A production-ready Python package for integrating A2A protocol agents into LangChain/LangGraph. Enables stateful conversations, streaming, multi-turn context management, and seamless LLM tool binding with A2A agents.

A comprehensive travel planning system built with Agent2Agent (A2A) protocol, featuring specialized AI agents for hotel booking, car rentals, currency conversion, and travel coordination.

Production-ready A2A Protocol Server with dual protocol support (HTTP REST + JSON-RPC 2.0). Built on SceneGraphManager v2.0.0 for JSON-driven AI workflow orchestration with LangGraph.

A multi-agent AI system that scans websites for security vulnerabilities. It uses the A2A (Agent-to-Agent) protocol for orchestration and MCP (Model Context Protocol) for tool integration. Specialized agents work together: they gather threat intel, crawl the site, analyze vulnerabilities, and produce a report.

The open-source event bus for AI agents. Webhooks in. Agent actions out.

A lawyer for the agent economy. AI agents can request contract review, risk analysis, and legal guidance via A2A protocol.