read-mas
READ-MAS generates software requirements specifications (SRS) and system designs from natural language queries using multi-agent AI orchestration built on Google ADK.
- 起点
- github
- 言語
- Jupyter Notebook
KoPass 公開カタログで測定された A2A リポジトリ。
READ-MAS generates software requirements specifications (SRS) and system designs from natural language queries using multi-agent AI orchestration built on Google ADK.
Durable, authenticated, and optionally federated routing for A2A Protocol agents.
React components for viewing ORD (Open Resource Discovery) Overlay 0.1 documents.
Open protocol for posted-price, verifiable work contracts between customers and autonomous agent orchestrators.
Temporary Adapter for connecting existing HTTP, command, Codex, and A2A backends through the OpenLinker Go SDK Runtime Worker.
Self-hosted Next.js UI for OpenLinker Core: Agent registry, User Tokens, runs, Runtime Worker setup, A2A/MCP tools, and administration.
Official Go SDK for OpenLinker Core: Agent discovery, runs, SSE, webhooks, A2A clients, and a durable mTLS Runtime Worker.
Official TypeScript SDK for OpenLinker Core: Agent calls from browsers and Edge runtimes, runs, SSE, webhooks, A2A, and a server-only durable Runtime Worker.
OpenWOP: the open-source protocol for multi-agent workflow orchestration. Run AI agents as workflows you can watch, pause for human approval and replay, on any host that implements it. Spec CC BY 4.0, code Apache 2.0.
One API to access all agents — an open directory + unified gateway for AI agents, plus thousands of OpenClaw skills for your coding agent.
SINCOR2 is a production-grade, full-stack autonomous agent platform designed to orchestrate, secure, and settle high-frequency Agent-to-Agent (A2A) commerce on BASE to operate independently of human intervention.
A2A-protocol bridge for two Claude Code agents communicating via MCP (Google Agent2Agent over JSON-RPC, exposed as stdio MCP tools).
Centralized Agent2Agent (A2A) Discovery Hub & Registry built with Java 21, Spring Boot 3.4, LangChain4j, PostgreSQL pgvector & Vue 3
🎥 Summarize YouTube videos into clear, actionable insights with AI, allowing you to grasp key points quickly and easily.
Loop Studio - A Loop Engineering Engine with Verify-Separation and Quality Gates for Multi-Agent Software Delivery
An MCP-native agentic control plane that installs into your own Google Cloud project in one command. Serverless git over Firestore and GCS, post-quantum encryption at rest, and a signed, journalled audit trail behind every privileged action.
Official JavaScript SDK for the PCH AI gateway - pay-per-inference billing in USDC on Base L2, autonomous agent key provisioning, and agent certification.
Official Python SDK for the PCH AI gateway - pay-per-inference billing in USDC on Base L2, autonomous agent key provisioning, and agent certification.
The open-source identity & trust platform for AI Agents — cryptographic identity, reputation scoring, and cross-protocol agent directory
Durable A2A coordination with opt-in Markdown memory, offline inboxes, knowledge graph and timeline, plus authorized Qdrant hybrid retrieval.
Network-layer authorization for AI agent traffic using the Gemini Enterprise Agent Platform with PingAuthorize / PingOne Authorize as the Policy Decision Point.
"Multi-agent cryptographic session — co-signed A2A handshakes for AI agent collaboration"
An intelligent, multi-agent customer support system powered by AI that automatically routes and handles customer inquiries through specialized agents. Built with Streamlit, Groq API, and a custom Agent-to-Agent (A2A) communication protocol.
The reliability and interoperability layer for AI agents. A2A-native. MCP-bridged.
Agent skills for Primitive — primitive-chat (email another agent and wait for the reply) and primitive-inbox (a managed inbox that receives mail). Works with Claude Code, Codex, Cursor, and 50+ agents.
ROAR (Real-time Open Agent Runtime) — Unified protocol for agent communication. Combines MCP + A2A + ACP + ANP into one standard.
AFIX: A protocol-agnostic Agentic Financial Interoperability eXchange. Schemas, research, and pilot design for cross-enterprise agentic governance interchange.
Provider-neutral, OS-neutral AI orchestration runtime for long-horizon missions, dynamic agent teams, local/cloud models, MCP, A2A, CLI, browser and desktop capabilities.
An AI-powered multi-agent system designed to support users through emotional recovery after a breakup. The team consists of specialized agents—Therapist, Closure Writer, Routine Planner, and Brutal Honesty Advisor. The system utilizes vision capabilities.
AI article explainer agent that combines multiple specialist perspectives (Developer, Summarizer, Explainer, Analogy Creator, Vulnerability Expert) to provide comprehensive article analysis and explanations.
This project builds an intelligent financial analysis agent that combines real-time market data and web search to generate structured, data-driven insights. It presents financial information in clear tables and concise summaries through an interactive playground interface.
AI Financial Coach Agent is a personalized financial advisor that analyzes user income, expenses, debts, and goals to provide actionable recommendations for budgeting, savings, and debt reduction. Using a multi-agent system
Investment analysis agent that fetches market data, financial statements, sentiment indicators, and technical analysis to generate comprehensive investment reports
The AI Meme Generator Agent is a powerful browser automation tool that creates memes using AI agents. This app combines multi-LLM capabilities with automated browser interactions to generate memes based on text prompts through direct website manipulation.
The news-agents project represents a sophisticated implementation of terminal-based multi-agent coordination for news aggregation
AI System Architect Advisor is an AI-powered system design assistant that transforms natural language project requirements into structured architecture recommendations, infrastructure planning, security strategies, and compliance considerations.
A hands-on tutorial implementation of Google's Agent2Agent (A2A) protocol. Three multi-agent travel planners Flight, Hotel, and Itinerary collaborate via Agent Cards, SSE streaming, and artifact passing. Includes LangGraph and CrewAI integrations.
A local A2A event and continuity service for agent applications, with structured history, provenance-safe transcripts, literal search, and natural-language queries.
Multi-agent AI system with Google ADK + A2A protocol: Researcher → Judge → Content Builder pipeline on Cloud Run. Reference implementation with full docs for LLMs and developers.
MCP-based agentic AI system enabling LLMs to fetch and reason over real-time global weather data using standardized tool invocation. Built with MCP Server/Client, Llama 3, and external APIs to deliver low-latency, hallucination-free weather intelligence through protocol-driven workflows.
Shared memory and switchboard for teams whose members each run their own AI agents. Meetings → decisions and action items, team knowledge graph, MCP tool surface, A2A broker with human oversight.
Production-ready A2A (Agent-to-Agent) protocol implementation for building multi-agent AI systems
an open protocol for personal agent-to-agent communication: two AI agents, each acting for one human, exchange end-to-end-encrypted messages.
AEL v0.13 public agent-native blockchain devnet: useful work, portable memory, resilient replicas, and deterministic mainnet readiness
FastAPI endpoints protected by x402 micropayment rail on Base/Solana
A private line between your agent and your friend's agent. Direct agent-to-agent messaging over your own tunnel — no Slack, no shared channel, no context loss.
A clean reference implementation of the Agent-to-Agent (A2A) protocol: specialized AI agents that discover each other and collaborate over JSON-RPC 2.0. Python · FastAPI · Pydantic.
Agent-to-agent paid data marketplace MCP server: two-person (dyadic) 4D motion capture in a shared coordinate frame, rehab biomechanics, threat intelligence, and commercial-carrier truck-sighting intelligence (RTK Spotter). 21 tools. Gasless USDC via x402.
Handbook técnico aberto sobre engenharia de IA em produção: ML tradicional, LLMs, RAG, agentes, segurança, observabilidade, FinOps e deployment.