MetaGPTTest
开源多Agent智能体协作框架MetaGPT核心概念介绍及相关案例测试
从实际使用的角度考虑，一个智能体要对我们有用，它必须具备哪些基本要素呢？ 从MetaGPT的观点来看，如果一个智能体能够执行某些动作（无论是由LLM驱动还是其他方式），它就具有一定的用途 简单来说，定义智能体应该具备哪些行为，为智能体配备这些能力，我们就拥有了一个简单可用的智能体 Action Action类是动作的逻辑抽象 Role Role类是智能体的逻辑抽象 一个Role能执行特定的Action，拥有记忆、思考并采用各种策略行动 基本上，它充当一个将所有这些组件联系在一起的凝聚实体 role.run() 运行角色后智能体则开始工作，只需要初始化它并使用一个起始消息运行它 一个智能体运行周期的流程图
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/nangeplus-metagpttest — read its card at https://meshkore.com/agent/nangeplus-metagpttest/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/nangeplus-metagpttestFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/nangeplus-metagpttest/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own MetaGPTTest?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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