A single interface to use and evaluate different agent frameworks
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Updated
Jun 20, 2025 - Python
A single interface to use and evaluate different agent frameworks
A decentralized agent network for building collaborative, LLM-powered agent-to-agent (A2A) systems.
Multi-Agent Systems with Google's Agent Development Kit + A2A + MCP
AgentX python SDK. Build multi-agent AI workforce.
The UnisonAI Multi-Agent Framework (A2A) provides a flexible and extensible environment for creating and coordinating multiple autonomous AI agents. UnisonAI is designed with flexibility and scalability in mind.
"Open-source toolkit (Python Library, Registry API, CLI) for secure, decentralized AI agent interoperability using A2A/MCP."
Multi-Agent Systems with Google's Agent Development Kit + A2A + MCP
Build and deploy an autonomous Devto Agent capable of interacting with the Dev.to platform, powered by A2A (Agent-to-Agent) and MCP (Model Context Protocol)
A flexible foundation AI system for creating A2A-compatible autonomous AI agents that can collaborate, reason, and execute complex tasks through standardized agent-to-agent communication protocols.
kbs_agent_a2a 智能体协议适配中间件
"Open-source toolkit (Python Library, Registry API, CLI) for secure, decentralized AI agent interoperability using A2A/MCP."
Atlassian (Jira/Confluence) AI Agent powered by 1st Party MCP Server using OpenAPI Codegen, LangGraph and LangChain MCP Adapters. Agent is exposed on various agent transport protocols (AGNTCY Slim, Google A2A, MCP Server)
A production-ready agent server built with LangGraph that implements the Agent-to-Agent (A2A) protocol
Master AI Challenge is a repository with two hands-on coding challenges focused on Artificial Intelligence and automation. Designed for learners and developers, these challenges aim to strengthen skills in Python, Shell scripting, data processing, and workflow automation. Fork the repo, solve the challenges, and enhance your AI and coding expertise
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