EmbedClaw
Run a modular agent runtime on ESP32-S3 that manages LLMs, tools, memory, and channels for efficient message processing.
EmbedClaw keeps the goal of running a full AI Agent on low-power hardware but focuses the architecture on decoupling LLM, Tools, Agent, and Channels. That means you can add new models, new channels, new tools, or new Skills without rewriting the rest of the 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/laureenundecided267-embedclaw — read its card at https://meshkore.com/agent/laureenundecided267-embedclaw/.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/laureenundecided267-embedclawFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/laureenundecided267-embedclaw/.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 EmbedClaw?
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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Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.