memkv-lmcache 1.0.1

LMCache storage plugin that targets the MemKV context memory store; gives vLLM a MemKV-backed prefix cache via lmcache_connector.

memkv-lmcache

LMCache StoragePluginInterface backend that persists KV chunks in a remote MemKV cluster. Loaded as a vendor plugin via LMCache's storage_plugins dynamic loader — no patches to LMCache's tree.

vLLM gets a MemKV-backed prefix KV-state path for free through vllm/distributed/kv_transfer/kv_connector/v1/lmcache_connector.py — no separate vLLM connector package is required.

Build

cd lmcache-plugin
pip install maturin
maturin develop --release      # local dev install
# or
maturin build --release        # wheel under target/wheels/
pip install target/wheels/memkv_lmcache-*.whl

The wheel bundles a native PyO3 extension built from the same memkv-client crate the NIXL plugin and the sglang plugin use, so RDMA/TCP transport selection works the same way across all three.

Configure the MemKV connection

The plugin reads the standard MemKV config chain — MEMKV_CONFIG yaml first, then MEMKV_* env vars:

export MEMKV_SERVERS="10.0.0.10:9900,10.0.0.11:9900"
export MEMKV_RDMA_DEVICES="mlx5_0,mlx5_1"
export MEMKV_AUTH_KEY="<64-hex>"
# optional:
# export MEMKV_TRANSPORT=auto
# export MEMKV_CONFIG=/etc/memkv.yaml

Configure LMCache

Add the plugin to your LMCache yaml. max_local_cpu_size must be > 0 because the plugin uses LocalCPUBackend's allocator to stage retrieved tensors:

chunk_size: 64
local_cpu: true
max_local_cpu_size: 5
storage_plugins: memkv
extra_config:
  storage_plugin.memkv.module_path: memkv_lmcache.backend
  storage_plugin.memkv.class_name: MemKVStorageBackend

Launch vLLM with LMCache + MemKV

LMCACHE_CONFIG_FILE=/etc/lmcache.yaml \
KV_TRANSFER_CONFIG='{"kv_connector":"LMCacheConnectorV1","kv_role":"kv_both"}' \
vllm serve meta-llama/Llama-3-8B \
    --tensor-parallel-size 1 \
    --kv-transfer-config "$KV_TRANSFER_CONFIG"

LMCache's connector picks the storage_plugins entry up at startup and routes prefix KV reads/writes through MemKVStorageBackend.

What's implemented

Method	Status
contains	yes (in-process _meta check — a key only counts as present when its shape/dtype metadata is on file, so a fresh process reports miss for server-resident bytes it cannot reconstruct); batched_contains falls through to StoragePluginInterface's default loop
exists_in_put_tasks	yes (in-process tracking set)
batched_submit_put_task	yes (synchronous; returns None)
get_blocking	yes (requires prior put in this process — see Caveats)
remove	yes
pin / unpin	yes (presence-check only — wire layer has no per-client retention)
get_allocator_backend	yes (delegates to LocalCPUBackend)
close	yes

Caveats

• Cross-restart warm cache is MVP-restricted. Each engine process keeps shape/dtype/fmt in an in-memory dict so get_blocking knows what MemoryObj to allocate. The wire bytes survive in MemKV across restarts; the local metadata does not. A fresh process therefore starts cold even when MemKV holds the chunks. This matches LMCache's LocalDiskBackend behavior. Encoding the shape header on the wire is a follow-up.
• Key length cap. MemKV's protocol caps keys at 512 bytes; CacheEngineKey.to_string() shapes longer than 480 bytes collapse to a memkv-h2:<blake2b-256> digest.
• Pin/unpin are local-only. MemKV has no per-client retention policy, so the methods are presence checks against the local meta dict. Server-side eviction is owned by the MemKV cluster.
• Reads ride the server-driven chunked BatchRead. get_blocking uses batch_get_into, which streams the full value through the server's bounce buffers into per-thread staging with strict full-length-or-miss semantics. The single-key zero-copy get_into (client-driven RDMA READ) remains available but is not the LMCache default: under sustained burst load it saturated the per-connection RC send CQ tail and tripped vLLM's SPMD broadcast timeout, and it faults the value resident server-side.

Layout

lmcache-plugin/
├── Cargo.toml                      # cdylib + pyo3 + memkv-client
├── pyproject.toml                  # maturin
├── src/lib.rs                      # PyO3 wrapper around memkv-client::Engine
└── python/memkv_lmcache/
    ├── __init__.py                 # re-exports Client
    └── backend.py                  # MemKVStorageBackend(StoragePluginInterface)