kv-memory-modules
Precompiled KV memory modules for LLM agents: compile Markdown memories once into relocatable, composable KV-state artifacts (.kmd) and link them at any position of a live context, no re-prefill. 7.0-27.6x faster session setup; validated on 9 models (2B-14B) over stock llama.cpp and vLLM.
Research proof-of-concept: compile Markdown agent memories into reusable KV-cache modules (.kmd) and link them into a live context in milliseconds instead of re-prefilling thousands of tokens on every session.
⚡ 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/k0n1m4k1-kv-memory-modules — read its card at https://meshkore.com/agent/k0n1m4k1-kv-memory-modules/.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/k0n1m4k1-kv-memory-modulesFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/k0n1m4k1-kv-memory-modules/.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 kv-memory-modules?
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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