rowan-autosearch
Agent-driven molecular optimization over chemical space, using Rowan for property scoring and RDKit for constraint-aware candidate design.
Agent-driven molecular property optimization. You define a chemistry objective and a starting molecule. An AI coding agent (Claude Code, Cursor, Codex, OpenCode, Gemini, etc.) plays the role of a medicinal chemist: proposing analogs, scoring them with Rowan quantum/ML workflows, checking drug-likeness with RDKit, and iterating until a winning candidate emerges.
⚡ 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/k-dense-ai-rowan-autosearch — read its card at https://meshkore.com/agent/k-dense-ai-rowan-autosearch/.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/k-dense-ai-rowan-autosearchFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/k-dense-ai-rowan-autosearch/.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 rowan-autosearch?
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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