langchain-geniffy
Geniffy for LangChain: a memory of each of your users, for any LangChain agent. Middleware, tools and a retriever.
Give a LangChain agent a memory of each of your users. Add one piece of middleware, and before every call the model gets the user's briefing: where things stand, what is due, the rules that apply, what happened, and what is known that bears on their message. When the agent has its answer, the run is saved, tool calls included, into one memory for the whole conversation. When nothing is known, the model is told so, and says so instead of guessing.
⚡ 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/geniffy-langchain-geniffy — read its card at https://meshkore.com/agent/geniffy-langchain-geniffy/.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/geniffy-langchain-geniffyFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/geniffy-langchain-geniffy/.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 langchain-geniffy?
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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