awesome-a2a
Agent2Agent (A2A) – awesome A2A agents, tools, servers & clients, all in one place.
https://github.com/ai-boost/awesome-a2a
Last synced: 1 day ago
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💬 Community
- google/A2A GitHub Issues - For reporting bugs or suggesting protocol improvements.
- Private Feedback Form - Google form for private feedback.
- google/A2A GitHub Discussions - For general questions, ideas, and community discussions about the A2A protocol.
- google/A2A GitHub Issues - For reporting bugs or suggesting protocol improvements.
- google/A2A GitHub Discussions - For general questions, ideas, and community discussions about the A2A protocol.
- google/A2A GitHub Discussions - For general questions, ideas, and community discussions about the A2A protocol.
- A2A GitHub Issues - For reporting bugs or suggesting protocol improvements.
- A2A GitHub Discussions - For general questions, ideas, and community discussions about the A2A protocol.
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🎬 Demos & Examples
- Official Demo Video (Section Link) - Link to the video embedded in the official repository's README.
- Official Multi-Agent Web App (Python/Mesop) - Demonstrates the orchestrator agent interacting with multiple remote agents, rendering text, images, and forms. **Requires running Python code.**
- Agent2Agent (A2A) Samples - a2a](https://github.com/google-a2a) [](https://github.com/google-a2a/a2a-samples) - Official repository containing code samples and demos which use the Agent2Agent (A2A) Protocol.
- Official Multi-Agent Web App (Python/Mesop) - Demonstrates the orchestrator agent interacting with multiple remote agents, rendering text, images, and forms. **Requires running Python code.**
- Agent2Agent (A2A) Samples - samples?style=social)](https://github.com/a2aproject/a2a-samples) - Official repository containing code samples and demos which use the Agent2Agent (A2A) Protocol.
- Official Demo Video (Section Link) - Link to the video embedded in the official repository's README.
- Official Multi-Agent Web App (Python/Mesop) - Demonstrates the orchestrator agent interacting with multiple remote agents, rendering text, images, and forms. **Requires running Python code.**
- Agentic Frameworks on AWS - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-agentic-frameworks-on-aws) - Examples and reference architectures for building autonomous agents using popular frameworks on AWS, including an end-to-end serverless multi-agent system using the A2A Protocol. MIT-0.
- CoffeeShop Agent - agent?style=social)](https://github.com/thangchung/coffeeshop-agent) - A .NET Aspire demo application showcasing the Microsoft Agent Framework, MCP, A2A (via the official `a2a-dotnet` SDK), and AG-UI protocols in a multi-agent coffee shop simulation.
- Agentic Apps - apps?style=social)](https://github.com/agntcy/agentic-apps) - Collection of experimental and reference agent applications built on the A2A protocol and SDK, including multi-agent tourist scheduling, a network of assistants, AI-powered observability root-cause analysis, and multicluster remediation demos. Apache 2.0.
- A2A Mastra Demo - A demonstration of Agent-to-Agent (A2A) communication using the Mastra framework and Amazon Bedrock, featuring a hybrid Express gateway plus Mastra Dev Server architecture, workflow orchestration, real-time visualization, MCP integration, and Docker Compose deployment. MIT licensed.
- Strands Agent with AgentCore - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-strands-agent-with-agentcore) - Reference architecture for agentic AI chatbots with Strands Agents and Amazon Bedrock AgentCore, featuring multi-agent orchestration, MCP tools, A2A delegation to remote worker agents, and multimodal/voice interaction. MIT licensed.
- Knowsee - mehta](https://github.com/saahil-mehta) [](https://github.com/saahil-mehta/knowsee-public) - Full-stack reference implementation of a multi-agent conversational AI assistant using Google ADK, CopilotKit, AG-UI, A2A, and GenerativeUI, with Vertex AI RAG, BigQuery data analyst, production auth, and Terraform IaC. Includes a [live demo](https://knowsee-frontend-yrptvkizbq-ew.a.run.app). Apache 2.0.
- A2A Gateway on AWS - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-a2a-gateway) - Serverless A2A gateway reference architecture on AWS providing management, control, and data layers for enterprise agent deployments, with OAuth 2.0, SSE streaming, fine-grained access control, and Bedrock AgentCore Runtime support. MIT-0.
- Secure Multi-Agent Delegation Chains on AWS - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-agentic-delegation) - Reference architecture demonstrating Cedar-based permission attenuation for A2A and MCP agent interactions. Shows how delegation tokens narrow scope at each hop, enforce tamper-proof token chains, and emit audit logs across a Strands coordinator, Google ADK pricing agent, and LangGraph purchasing agent on Amazon Bedrock AgentCore. Includes local demo, 48 tests, Docker Compose, and AWS CDK deployment. MIT-0 licensed.
- Microsoft Build 2026: How Foundry Integrates With Open Source Frameworks and Tools - DEM333-how-foundry-integrates-with-open-source-frameworks-and-tools?style=social)](https://github.com/microsoft/Build26-DEM333-how-foundry-integrates-with-open-source-frameworks-and-tools) - Build 2026 demo building a practical OpenClaw-like agent with LangGraph, MCP, Playwright, OpenTelemetry, and A2A agent-to-agent communication, then operationalizing it in Microsoft Foundry. MIT licensed.
- Agent Interoperability (Multi-Cloud) - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-agent-interoperability) - Multi-cloud AI agent interoperability sample showing Google ADK and Strands Agents running on Amazon Bedrock AgentCore Runtime, exposed via the A2A protocol, with tools served through Bedrock AgentCore Gateway and MCP. Consumed from a React frontend and Gemini Enterprise. MIT-0 licensed.
- AgentCore Multi-Agent Framework & Protocol Workshop - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-multi-agent-framework-protocol-agentcore-workshop) - A hands-on workshop for building a production multi-agent AI system on Amazon Bedrock AgentCore. An orchestrator agent coordinates three specialists — each built with a different framework (Strands, LangChain) and protocol (HTTP, A2A, MCP) — to diagnose, analyze, and fix data pipeline issues. Covers Runtime, Gateway, Memory, Policy, and Evaluations.
- Bedrock AgentCore Enterprise Platform - samples](https://github.com/aws-samples) [](https://github.com/aws-samples/sample-agentcore-enterprise-platform) - Amazon Bedrock AgentCore enterprise platform accelerator with AWS CDK, Terraform organization guardrails, MCP/A2A agents, security, memory, and observability. Apache 2.0.
- Multi-Agent Travel Assistant - zhou](https://github.com/phoenix-zhou) [](https://github.com/phoenix-zhou/multi-agent) - A multi-agent travel assistant system built with A2A and MCP, featuring LLM-based intent routing, weather/flight/train/ticket query agents, booking orchestration, scenic recommendations, multi-turn dialogue, and both CLI and Streamlit Web interfaces.
- E-Commerce Agents - commerce-agents?style=social)](https://github.com/nitin27may/e-commerce-agents) - A multi-agent e-commerce platform built with the Microsoft Agent Framework where six specialized agents collaborate over A2A to handle product discovery, orders, pricing, reviews, inventory, and support. Ships with dual Python and .NET/C# backends, a Next.js generative-UI frontend, Docker Compose, and 34 tutorial chapters. MIT licensed.
- AtlasTrip - multi-agent-travel?style=social)](https://github.com/fnusatvik07/a2a-multi-agent-travel) - Five AI agents on five mutually incompatible frameworks (LangGraph, Google ADK, CrewAI, LlamaIndex, Pydantic AI) running as separate services that cannot import each other, cooperating over A2A v1.0 — task lifecycle, negotiation, and human-in-the-loop escalation — plus one shared MCP inventory server. A corporate travel desk demo with 158 passing tests, a narrated explainer video, and every figure taken from a real run. MIT licensed.
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🚀 Getting Started with A2A
- Official Demo Video - Agent Web App Demo](https://github.com/a2aproject/A2A/tree/v0.2.1/demo).
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⚙️ How Does A2A Work? (High Level)
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⚙️ Implementations & Libraries
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- trpc-a2a-go - group](https://github.com/trpc-group) [](https://github.com/trpc-group/trpc-a2a-go) - Go A2A implementation by the tRPC team featuring full client/server support, in-memory task management, streaming responses, session management, multiple auth methods (JWT, API Key, OAuth2), and comprehensive examples.
- a2a-go - go?style=social)](https://github.com/a2aserver/a2a-go) - A Go library for building A2A servers, with example implementations.
- a2a-rs - rs?style=social)](https://github.com/EmilLindfors/a2a-rs) - An idiomatic Rust implementation following hexagonal architecture principles.
- a2a_min - A minimalistic Python SDK for A2A communication.
- a2adotnet - A C#/.NET implementation of the A2A protocol.
- nestjs-a2a - a2a?style=social)](https://github.com/thestupd/nestjs-a2a) - A module for integrating the A2A protocol into NestJS applications.
- python-a2a - a2a?style=social)](https://github.com/themanojdesai/python-a2a) - An easy-to-use Python library for implementing the A2A protocol.
- Cognisphere - An AI agent development framework built on Google's ADK, facilitating agent creation potentially for A2A networks.
- Grasp - A Self-hosted Browser Using Agent with built-in MCP and A2A support.
- swissknife - A multi-agent chat application with MCP support, aiming to expose agents via the A2A protocol and connect to remote A2A agents as a client.
- Agentic - agentic?style=social)](https://github.com/jeremychone/rust-agentic) - A Rust crate providing essential building blocks for agentic applications, with an ergonomic API for MCP and A2A support. (Work in Progress)
- a2ajava - Java A2A server/client implementation using Spring Boot with annotations. Supports WebSockets, MCP integration, and includes enterprise/Kubernetes deployment tutorials.
- Elkar - ai](https://github.com/elkar-ai) [](https://github.com/elkar-ai/elkar-a2a) - An open-source task-management layer for AI agents — based on Google's Agent2Agent Protocol (A2A). Send, track, and orchestrate tasks across AI agents — effortlessly.
- https://github.com/google-a2a/a2a-samples/tree/main/samples/js
- https://github.com/google-a2a/a2a-samples/tree/main/samples/js/src/agents/movie-agent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/js/client
- https://github.com/google-a2a/a2a-samples/tree/main/samples/js/server
- https://github.com/google-a2a/a2a-samples/tree/main/samples/java/client
- https://github.com/google-a2a/a2a-samples/tree/main/samples/java/model
- https://github.com/google-a2a/a2a-samples/tree/main/samples/java/server
- https://github.com/google-a2a/a2a-samples/tree/main/samples
- https://github.com/google-a2a/a2a-samples/tree/main/samples/host\_agent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/weather\_agent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/a2a-mcp-without-framework
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/a2a\_telemetry
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/ag2
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/analytics
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/autogen
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/azureaifoundry\_sdk
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/birthday\_planner\_adk
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/calendar\_agent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/crewai
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/google\_adk
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/headless\_agent\_auth
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/helloworld
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/langgraph
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/llama\_index\_file\_chat
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/marvin
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/mindsdb
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/agents/semantickernel
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/travel\_planner\_agent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/veo\_video\_gen
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/hosts
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/hosts/multiagent
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/common
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/common/server
- https://github.com/google-a2a/a2a-samples/tree/main/samples/python/common/utils
- https://github.com/google-a2a/a2a-samples/tree/main/samples/go
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- a2a-python - python?style=social)](https://github.com/google/a2a-python) - **Official** Python SDK for running agentic applications as A2A servers following the Agent2Agent Protocol.
- A2AServer - A Python server framework implementing Google's A2A protocol with MCP integration.
- a2a-net - io](https://github.com/neuroglia-io) [](https://github.com/neuroglia-io/a2a-net) - .NET implementation of the Agent2Agent (A2A) protocol to enable secure, interoperable communication between autonomous agents across frameworks and vendors.
- Artinet SDK - artinet-project](https://github.com/the-artinet-project) [](https://github.com/the-artinet-project/artinet-sdk) - TypeScript (Node.js) A2A compliant server/client simplifying interoperable AI agent creation, focusing on DX and production-readiness.
- a2a4j - A2A4J is a comprehensive Java implementation of the Agent2Agent Protocol, including server, client, examples, and a starter — ready to use out of the box.
- n8n-nodes-agent2agent - nodes-agent2agent?style=social)](https://github.com/pjawz/n8n-nodes-agent2agent) - Adds nodes to n8n for interacting with AI agents using Google's Agent2Agent (A2A) protocol.
- a2a-python - python?style=social)](https://github.com/a2aproject/a2a-python) - **Official** Python SDK for running agentic applications as A2A servers following the Agent2Agent Protocol.
- adk-modular-architecture - jarzyna](https://github.com/k-jarzyna) [](https://github.com/k-jarzyna/adk-modular-architecture) - A Python project demonstrating a modular architecture for ADK (Agent Development Kit) based agents, with A2A protocol considerations.
- google-calendar-agent - gateway](https://github.com/inference-gateway) [](https://github.com/inference-gateway/google-calendar-agent) - A standalone A2A agent that can manage a user's Google Calendar, compatible with any OpenAI-compatible API for its LLM.
- A2AApp - An Agent2Agent (A2A) network built with Google Apps Script, enabling secure, decentralized AI communication and integration within Google Workspace as both an A2A server and client.
- a2a-go - go?style=social)](https://github.com/yeeaiclub/a2a-go) - Agent-to-Agent Protocol Implementation for Go, fully supports all methods of the A2A protocol, referring to the official Python SDK implementation.
- AgentUp - A developer-first, open-source AI agent framework designed to make agents portable, scalable, and secure. Features configuration-driven architecture, built-in OAuth2/JWT/API key authentication, automatic A2A discovery, asynchronous task management, and support for both A2A and MCP protocols. Built by engineers who've created open-source solutions powering mission-critical systems at Google, GitHub, Nvidia, Red Hat, Shopify and more.
- https://github.com/a2aproject/a2a-samples/tree/main/samples/js
- https://github.com/a2aproject/a2a-samples/tree/main/samples/js/src/agents/movie-agent
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/custom_java_impl/client
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/custom_java_impl/model
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/custom_java_impl/server
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- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/agents/magic_8_ball_security
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/agents/content_writer
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/agents/content_editor
- https://github.com/a2aproject/a2a-samples/tree/main/samples/java/agents/weather_mcp
- https://github.com/a2aproject/a2a-samples/tree/main/samples/dotnet/BasicA2ADemo
- https://github.com/a2aproject/a2a-samples/tree/main/samples/dotnet/A2ACliDemo
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- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/hosts/cli
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/helloworld
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- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/birthday_planner_adk
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- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/a2a_mcp
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/a2a-mcp-without-framework
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/travel_planner_agent
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/headless_agent_auth
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/analytics
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/a2a_telemetry
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/hosts/a2a_multiagent_host
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/github-agent
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/veo_video_gen
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- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/marvin
- https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents/mindsdb
- https://github.com/a2aproject/a2a-samples/tree/main/samples/go
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- a2a-js - js?style=social)](https://github.com/a2aproject/a2a-js) - **Official** JavaScript SDK for the Agent2Agent (A2A) Protocol.
- a2a-java - java?style=social)](https://github.com/a2aproject/a2a-java) - **Official** Java SDK for the Agent2Agent (A2A) Protocol.
- AG2 (AutoGen) - Open-source multi-agent framework with native A2A protocol support. Features A2aAgentServer for exposing AG2 agents as A2A services and A2aRemoteAgent for connecting to any A2A-compatible agent. Enables cross-framework interoperability (e.g., with Pydantic AI).
- a2a-go - go?style=social)](https://github.com/a2aproject/a2a-go) - **Official** Go SDK for the A2A Protocol with high-level server (`a2asrv`) and client (`a2aclient`) APIs, multi-transport support (gRPC, REST, JSON-RPC), extensible architecture, and a CLI tool for agent discovery and messaging.
- ra2a - Comprehensive Rust SDK for A2A v1.0 with all 12 JSON-RPC methods, gRPC/SSE streaming, pluggable storage (PostgreSQL/MySQL/SQLite), OAuth 2.0/mTLS security, OpenTelemetry tracing, and composable Axum handlers.
- jamjet-a2a - labs](https://github.com/jamjet-labs) [](https://github.com/jamjet-labs/jamjet-a2a) - Standalone Rust SDK for A2A v1.0 with client, server, coordinator routing, and MCP bridge. TCK conformant (75/76 mandatory). Two crates: `jamjet-a2a-types` (pure types, zero I/O) + `jamjet-a2a` (full SDK with feature flags).* **Python**
- fasta2a - Framework-agnostic Python A2A server library that lets developers expose agents through ASGI with pluggable storage, broker, and worker components.
- codex-a2a - a2a?style=social)](https://github.com/liujuanjuan1984/codex-a2a) - Full A2A Protocol implementation for Codex CLI, providing a stateful, production-oriented agent service with standardized transport and lifecycle mapping.
- opencode-a2a - Internet](https://github.com/Intelligent-Internet) [](https://github.com/Intelligent-Internet/opencode-a2a) - Full A2A Protocol implementation for OpenCode, providing a stateful A2A service with production-friendly deployment, auth, and session continuity.
- a2a - Ruby gem implementing A2A protocol data structures with serialization, validation, and case transformation support. Published on RubyGems.
- a2a-dotnet - dotnet?style=social)](https://github.com/a2aproject/a2a-dotnet) - **Official** C#/.NET SDK for the A2A Protocol.
- spring-ai-a2a - ai-community](https://github.com/spring-ai-community) [](https://github.com/spring-ai-community/spring-ai-a2a) - Spring Boot and Spring AI integration for building AI agent servers using the A2A Protocol. Features auto-configuration, full `@Tool` support, and multi-agent orchestration examples.
- a2a-4k - 4k](https://github.com/a2a-4k) [](https://github.com/a2a-4k/a2a-4k) - Kotlin implementation of the A2A protocol with client/server modules, Ktor-based server support, Redis-backed task storage, streaming support, and examples for Arc and LangChain4j integrations.
- a2a-swift - Apps](https://github.com/Victory-Apps) [](https://github.com/Victory-Apps/a2a-swift) - A Swift SDK for A2A with full v1.0 data model, JSON-RPC routing, SSE streaming with reconnection, Vapor integration, and testing utilities. Supports macOS, Linux, iOS, tvOS, watchOS.
- a2a-elixir - elixir?style=social)](https://github.com/actioncard/a2a-elixir) - Elixir implementation of the A2A protocol with behaviour-based GenServer agents, multi-turn conversations, SSE streaming, HTTP serving via Plug, skill-based agent registry, pluggable storage, and Telemetry integration.
- a2a_ex - Elixir client and server library for A2A with REST/JSON-RPC transports, SSE streaming utilities, Plug integration, typed structs, task store abstractions, and protocol compatibility modes.
- AgentUp - further](https://github.com/always-further) [](https://github.com/always-further/AgentUp) - A developer-first, open-source AI agent framework designed to make agents portable, scalable, and secure. Features configuration-driven architecture, built-in OAuth2/JWT/API key authentication, automatic A2A discovery, asynchronous task management, and support for both A2A and MCP protocols.
- AgentAnycast - A decentralized P2P runtime for the A2A protocol, powered by libp2p. Features end-to-end encryption (Noise_XX), automatic NAT traversal, skill-based anycast routing, MCP tool bridging, and framework adapters (CrewAI, LangGraph). Zero-config — agents communicate across any network without public IPs or VPNs. SDKs for Python and TypeScript.
- a2a-client-hub - client-hub?style=social)](https://github.com/liujuanjuan1984/a2a-client-hub) - A self-hosted A2A client hub for teams and individuals to manage, invoke, and operate multiple A2A agents across web and mobile with unified session history and governance.
- a2a-rust - Pure Rust SDK for A2A v1.0 with quad transport (JSON-RPC/REST/WebSocket/gRPC), SSE streaming, agent card signing (JWS/ES256), pluggable stores (SQLite/PostgreSQL), multi-tenancy, and TCK conformance. Published on crates.io as `a2a-protocol-sdk`.
- awaken - A Rust agent runtime that serves AI SDK, CopilotKit, A2A, and MCP from the same backend, featuring type-safe state, streaming LLM failure recovery, and plugin extensibility. Published on crates.io.
- turul-a2a - a2a?style=social)](https://github.com/aussierobots/turul-a2a) - Proto-first Rust SDK for A2A v1.0 with ergonomic server/client crates, pluggable storage (SQLite/PostgreSQL/DynamoDB), multi-transport support (HTTP/JSON-RPC/SSE/gRPC/AWS Lambda), JWT/API-key auth, and interoperability-tested against the official Go SDK. Published on crates.io.
- a2a-adapter - adapter?style=social)](https://github.com/hybroai/a2a-adapter) - Python SDK that converts agents from n8n, LangGraph, CrewAI, LangChain, Claude Code, Codex, Ollama, and more into A2A-compatible servers with auto-generated AgentCards and streaming support. Published on PyPI.
- agent-protocol - ai](https://github.com/openJiuwen-ai) [](https://github.com/openJiuwen-ai/agent-protocol) - C++ SDK for the Agent2Agent (A2A) Protocol (and MCP), providing implementations of agent communication protocols for C++ environments.
- a2a-ai-provider - ai-provider?style=social)](https://github.com/DracoBlue/a2a-ai-provider) - Community A2A provider for the Vercel AI SDK, enabling drop-in interoperability with A2A agents via `generateText` and `streamText`.
- a2a-mesh - mesh?style=social)](https://github.com/oaslananka/a2a-mesh) - Production-ready TypeScript runtime for Google's A2A Protocol with multi-framework adapters, registry control plane, JWT/API-key auth, OpenTelemetry observability, CLI scaffolding, and testing toolkit. Published on npm.
- a2a-php - php?style=social)](https://github.com/andreibesleaga/a2a-php) - PHP implementation of the A2A Protocol with a fully compliant reference server, strict JSON-RPC validation, task management, SSE streaming, push notifications, and 100% official TCK pass rate.
- a2a - Dart/Flutter SDK for the A2A protocol, modelled after the official `a2a-js` SDK. Provides an `A2AClient` with JSON-RPC, SSE streaming, push notification configuration, agent card retrieval, plus a CLI client and server-side support. Published on pub.dev as `a2a` by verified publisher `darticulate.com`; runs on Android, iOS, Linux, macOS, and Windows.
- ANT AI - idsia](https://github.com/idea-idsia) [](https://github.com/idea-idsia/ant-ai) - A lightweight Python framework from IDSIA for building tool-driven AI agents and multi-agent systems with first-class A2A protocol support (dedicated `a2a` module with client, server, executor, session, and translator). Features graph-based workflow orchestration, MCP tool integration, lifecycle hooks for guardrails, LLM-agnostic core, and built-in observability via Langfuse. MIT licensed and published on PyPI as `ant-ai`.
- google-maps-a2a - maps-a2a?style=social)](https://github.com/pab1it0/google-maps-a2a) - An open-source A2A-compliant server that provides Google Maps capabilities — geocoding, reverse geocoding, directions, places search, and distance matrix — to other agents via the standardized protocol.
- routa - Workspace-first multi-agent coordination platform for AI development, with shared Specs, Kanban orchestration, and MCP/ACP/A2A support across web and desktop.
- OpenClaw A2A Gateway - a2a-gateway?style=social)](https://github.com/win4r/openclaw-a2a-gateway) - Production-ready OpenClaw plugin implementing the A2A protocol with bidirectional agent communication, adaptive bio-inspired routing, auto-discovery (DNS-SD/mDNS), and resilient multi-transport support (JSON-RPC, REST, gRPC).
- UnifAI - community-ai-tools](https://github.com/redhat-community-ai-tools) [](https://github.com/redhat-community-ai-tools/UnifAI) - Production-grade multi-agent orchestration engine with A2A and MCP protocol support. Features a pluggable catalog of Agents, LLMs, tools, and retrievers, built-in RAG pipeline for enterprise knowledge retrieval, and a visual drag-and-drop blueprint builder. Execute locally with LangGraph or distributed with Temporal.
- Hector - An A2A-Native AI Agent Platform written in Go. One self-contained binary, one YAML config, production-ready defaults. Deploy on-premise, in air-gapped environments, or in any cloud with zero external dependencies and zero telemetry. A2A v0.3.0 compliant.
- E.D.D.I - Production-grade, config-driven multi-agent orchestration middleware for conversational AI (Java/Quarkus). Features native A2A and MCP protocol support, 12+ LLM providers, RAG, persistent memory, and enterprise compliance. Ships as a Red Hat-certified Docker image.
- TrainPPTAgent - Template-based PPT generation system powered by A2A, ADK, and MCP. Features a Vue.js frontend, Python FastAPI backend, and GRPO reinforcement learning for optimized content generation.
- ContextForge - context-forge?style=social)](https://github.com/IBM/mcp-context-forge) - Open-source AI Gateway, registry, and proxy that federates MCP, A2A, and REST/gRPC services into a unified endpoint with centralized discovery, governance, and observability. Includes a dedicated Agent Gateway routing A2A protocol traffic alongside OpenAI/Anthropic agents, plus JWT/SSO/RBAC auth, OpenTelemetry tracing, plugin extensibility, sample A2A agents, and Helm/Kubernetes deployment. Apache 2.0, published on PyPI as `mcp-contextforge-gateway` and as a container on GHCR.
- agent-sdk-go - sdk-go?style=social)](https://github.com/agenticenv/agent-sdk-go) - Production-grade Go SDK for durable AI agents built on Temporal workflows. Features first-class A2A server/client, MCP, AG-UI streaming, sub-agents, human-in-the-loop, and OpenTelemetry. Survives crashes and deploys automatically.
- a2a-rs - rs?style=social)](https://github.com/a2aproject/a2a-rs) - **Official** Rust SDK for the A2A Protocol. Workspace-based implementation with core types, async client/server, gRPC/SLIMRPC bindings, SSE streaming, protobuf interop, and a CLI tool.
- a2a-cpp - cpp?style=social)](https://github.com/MisterVVP/a2a-cpp) - C++20 SDK for the Agent2Agent (A2A) Protocol with client/server APIs, discovery, REST/JSON-RPC/gRPC transports, streaming, authentication hooks, and CMake/vcpkg/Conan build integration.
- a2a-reference-ts - reference-ts?style=social)](https://github.com/reaatech/a2a-reference-ts) - Production-ready TypeScript reference implementation of Google's A2A protocol with server framework (Express/Hono adapters), client SDK, bidirectional A2A ↔ MCP bridge, canonical Zod schemas, pluggable auth (OAuth2/JWT/API key), Redis/Postgres persistence, SSE streaming, and OpenTelemetry observability. Published on npm as `@reaatech/*`.
- Agenspy - A protocol-first AI agent framework built on top of DSPy, designed to create sophisticated, production-ready AI agents with native support for MCP and Agent2Agent protocols. Features comprehensive CLI, Python & JavaScript MCP servers, and automatic connection management. MIT licensed and published on PyPI as `agenspy`.
- ProtoLink - A lightweight Python framework that implements and extends Google's A2A specification at the wire level, providing a unified agent runtime with built-in client/server, swappable transports (HTTP/WebSocket/gRPC/in-memory), native LLM and MCP tool integration, OAuth2/API-key auth, structured deterministic flows (Pipeline/Parallel/Router/Graph), and Langfuse/LangSmith telemetry. MIT licensed and published on PyPI as `protolink`.
- inference-gateway/adk - gateway](https://github.com/inference-gateway) [](https://github.com/inference-gateway/adk) - A Go-based Agent Development Kit for building A2A-compatible agents with full protocol compliance, multi-LLM provider support (OpenAI, Ollama, Groq, Cohere), real-time streaming, OIDC/OAuth2 auth, push notifications, lifecycle callbacks for guardrails/caching/logging, file artifacts with filesystem and MinIO backends, task pausing and resumption, pluggable storage (in-memory/Redis), TLS, OpenTelemetry observability, and 14+ working examples. MIT licensed.
- Hyperterse - A Go agentic server framework that ships declarative A2A agents (built on the official `a2aproject/a2a-go` SDK with per-agent JSON-RPC endpoints at `/agent/{name}`, agent cards, messaging, tasks, and streaming) alongside a full MCP server (tools/resources/prompts/completion to MCP spec 2025-11-25) from a single config-driven runtime. Features filesystem-based tool/agent/prompt discovery, database adapters (PostgreSQL/MySQL/SQLite/libSQL/MongoDB/Redis) exposed as typed MCP tools, optional TypeScript handlers for custom logic, multi-LLM providers (OpenAI-compatible + Gemini/Vertex), per-tool API-key auth plugins, in-memory caching, and OpenTelemetry tracing/metrics. Apache 2.0.
- Mangaba AI - ai](https://github.com/Mangaba-ai) [](https://github.com/Mangaba-ai/mangaba_ai) - A professional Python multi-agent orchestration framework with native A2A and MCP protocol support, ReAct reasoning, function calling, RAG, persistent memory, advanced vector stores, and resilient multi-provider LLM interoperability. MIT licensed and published on PyPI as `mangaba`.
- Agentic Kernel - kernel?style=social)](https://github.com/Qredence/agentic-kernel) - A flexible foundation AI system for creating A2A-compatible autonomous AI agents that can collaborate, reason, and execute complex tasks. Built on Google's A2A standard and the ADK framework, featuring a modular multi-agent architecture, sophisticated workflow engine, dynamic planning with an Orchestrator Agent, and a Chainlit-based interactive UI. MIT licensed and published on PyPI as `agentic-kernel`.
- Reactive Agents - agents-ts?style=social)](https://github.com/tylerjrbuell/reactive-agents-ts) - A composable TypeScript AI agent framework with end-to-end Effect-TS type safety, a deterministic 12-phase execution engine, 5 reasoning strategies (ReAct, Reflexion, Plan-Execute, Tree-of-Thought, Adaptive), persistent 4-tier memory, production guardrails, cost routing, and native A2A protocol support (Agent Cards, JSON-RPC 2.0 server/client, SSE streaming). 5,000+ tests, 35 packages. MIT licensed and published on npm as `@reactive-agents/*`.
- Swarm - A Rust framework for building and orchestrating intelligent multi-agent systems through open standards (A2A and MCP). Features a Planner Agent that produces static or dynamically generated workflows, an Executor Agent that carries them out with a built-in LLM-as-a-Judge evaluation loop for self-correction, an Agent Factory for programmatic agent instantiation at runtime, specialized Domain Agents, and an MCP Runtime that bridges agents to external tools. Workspace-organized crates built on `a2a-rs` and `rmcp`. Apache 2.0.
- LLM Tornado - A .NET provider-agnostic SDK for building, orchestrating, and deploying AI agents and workflows with first-class A2A protocol support via the dedicated `LlmTornado.A2A` package (AgentCard discovery, message send, SSE streaming, task lifecycle) and a companion `LlmTornado.A2A.AgentServer` for exposing Tornado agents as A2A servers. Features 30+ built-in LLM/vector DB connectors (OpenAI, Anthropic, Google, Cohere, xAI, Mistral, vLLM, Ollama, etc.), graph-based agent orchestration (Orchestrator/Runner/Advancer with handoffs and parallel execution), MCP integration, Anthropic Skills, multimodal I/O, and Microsoft.Extensions.AI interop. 100,000+ NuGet installs, 500+ tests. MIT licensed (license-stable commitment) and published on NuGet as `LlmTornado.*`.
- trpc-agent-go - group](https://github.com/trpc-group) [](https://github.com/trpc-group/trpc-agent-go) - A powerful Go framework for building intelligent agent systems with first-class A2A interoperability. Features A2A server (one-click exposure of any agent as an A2A service with auto-generated AgentCards), A2AAgent client proxy for calling remote A2A agents, automatic bidirectional message protocol conversion, streaming and non-streaming modes, multi-agent orchestration (chain/parallel/graph-based workflows), persistent memory, prompt caching, and built-in telemetry. Published on pkg.go.dev. Apache 2.0.
- Atmosphere - JVM runtime for streaming, governable AI agents with first-class A2A, MCP, and AG-UI protocol support. Declare behavior with @Agent and deliver over WebSocket, SSE, gRPC, and WebTransport/HTTP3. Features runtime adapters for Spring AI, LangChain4j, Google ADK, and Quarkus, plus policy admission, human-in-the-loop approvals, and durable sessions. Apache 2.0.
- Aser - A lightweight, modular Python AI agent framework with first-class Google A2A protocol support (server/client examples built on the official `a2a-sdk`), plus MCP, memory, RAG, and multi-agent orchestration. MIT licensed and published on PyPI as `aser`.
- RustyHand - Open-source Agent OS in Rust (124K LOC, 1,577 tests, zero clippy warnings). One ~32MB binary with autonomous agents, 61 built-in tools, 26 LLM providers, 37 channel adapters (Telegram/Discord/Slack...), MCP server, and A2A protocol endpoints for cross-instance agent communication.
- ISEK - Decentralized agent-to-agent network framework for cooperative AI societies, combining Google's A2A protocol with ERC-8004 smart contracts for on-chain agent identity, reputation, and trust. Provides local agent hosting, P2P relay via libp2p for NAT-traversed peer connections, an Agent Explorer for discovery, and a sample multi-agent ChatApp. Published on PyPI as `isek` and MIT licensed.
- AgentScope Runtime - ai](https://github.com/agentscope-ai) [](https://github.com/agentscope-ai/agentscope-runtime) - Production-grade runtime framework for agent applications with native A2A protocol support — A2A protocol adapter, Nacos-based A2A agent registry, and Agent-as-a-Service (AaaS) deployers that automatically expose A2A endpoints with SSE streaming. Features secure tool sandboxing (Python/Shell/GUI/Browser/Filesystem/Mobile), framework-agnostic adapters (AgentScope, Agno, AutoGen, LangGraph, Microsoft Agent Framework), full-stack observability, and multi-target deployment (local, Kubernetes, Knative, OpenKruise, Function Compute, serverless). Apache 2.0 licensed and published on PyPI as `agentscope-runtime`.
- Zeph - ops](https://github.com/bug-ops) [](https://github.com/bug-ops/zeph) - Memory-first Rust AI agent runtime for long-running work with a dedicated `zeph-a2a` crate implementing the A2A protocol (JSON-RPC 2.0, agent discovery via `/.well-known/agent.json`, SSE streaming, bearer auth, and Invocation-Bound Capability Tokens). Features temporal graph memory, self-learning skills, multi-model cascade routing (Ollama / Claude / Gemini / OpenAI / GGUF / TEE), sub-agents, MCP + ACP integration, sandboxed tools, CLI, and TUI. Published on crates.io as `zeph` (with `zeph-a2a` as a feature-gated standalone crate). MIT licensed.
Programming Languages
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⚙️ Implementations & Libraries
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