memagent-local
Local-first layered memory and autonomous learning engine
字符 n-gram 嵌入对措辞敏感——记忆存"我昨天去吃了火锅"，用户问 "昨天中午用餐了吗"可能漏检。memagent/synonyms.py::expand_query 对查询 生成检索变体，retrieve 对每条记忆取变体相似度的最大值（原始查询恒在 变体里，故 rel 只会升不会降）：
⚡ 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/memagent-contributors-memagent-local — read its card at https://meshkore.com/agent/memagent-contributors-memagent-local/.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/memagent-contributors-memagent-localFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/memagent-contributors-memagent-local/.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 memagent-local?
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.