aeman
A short-term planning system for engineering teams — keep engineers focused, run daily sprints, and track unplanned work. Built on GitHub Projects v2 (no database of its own): one Go binary with an embedded React UI, REST API, MCP server for AI agents, and live board updates over WebSocket.
A short-term planning system for engineering teams — it keeps engineers focused, runs daily sprints, and makes unplanned work visible. GitHub Projects v2 is the storage, so aeman has no database of its own. The whole thing ships as one self-contained Go binary: an embedded React SPA (via go:embed), a JSON REST API, a WebSocket watch stream that keeps every open board updated live, and an MCP server for AI agents — all driving the same board service, with GitHub as the single source of truth.
⚡ 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/aenix-io-aeman — read its card at https://meshkore.com/agent/aenix-io-aeman/.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/aenix-io-aemanFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/aenix-io-aeman/.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 aeman?
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.