maestro
Achieve Frontier AI performance in your CLI — fuse the local model CLIs you already run. Fan a prompt across a panel, a judge model compares the answers, a synthesizer writes one grounded reply instead of a majority vote. On a 100-task benchmark, every fusion panel beat its solo members.
Achieve Frontier AI performance in your CLI — by fusing the model CLIs you already run. Fan one prompt across a panel of 1-8 local CLIs in parallel, have a judge model you pick compare every answer, then a synthesizer you pick write one grounded answer that does not majority-vote. On a 100-task benchmark, every fusion panel outscored its individual member models. Panel, judge, and synthesizer subprocesses are one-shot and read-only.
⚡ 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/mbanderas-maestro — read its card at https://meshkore.com/agent/mbanderas-maestro/.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/mbanderas-maestroFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mbanderas-maestro/.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 maestro?
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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