OpenClaw-Internals
OpenClaw source code architecture analysis of a production AI Agent gateway — Agent Loop, memory, tool sandbox, custom WebSocket protocol, 20+ IM adapters. 从 Agent Loop、记忆系统、工具沙箱到自研 WebSocket 协议 —— 拆解一个真正跑在生产环境中的多通道 AI Agent 网关是如何设计与实现的。
OpenClaw Internals is the answer set to these questions. This is not a usage manual — it's a source-code-level architectural analysis of a production-grade AI Agent system by OpenClaw's core development team. Every article directly references source files and key functions, revealing the real engineering decisions behind a live system.
⚡ 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/botx-work-openclaw-internals — read its card at https://meshkore.com/agent/botx-work-openclaw-internals/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/botx-work-openclaw-internalsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/botx-work-openclaw-internals/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own OpenClaw-Internals?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.