A field survey of released kind: "memory" plugins for OpenClaw — what ships today, what's still beta, and what's mostly a GitHub thread.
OpenClaw exposes exactly one exclusive memory slot: plugins.slots.memory = "<plugin-id>". A plugin has to declare kind: "memory" to own it, and only one at a time can. The bundled default is memory-core — SQLite plus FTS5 plus sqlite-vec. Everything else in the ecosystem falls into one of three buckets, and only the first is in scope here.
kind: "memory" and replace memory-core when activated via plugins.slots.memory.memory-wiki (bundled companion, lives beside the slot owner); QMD (a sidecar binary used as a backend by memory-core when you set memory.backend: "qmd", not a slot plugin); Lossless Claw (owns the contextEngine slot, not the memory slot); Hindsight (runs as a LaunchAgent, entirely outside the plugin system).memory-redis (closed by maintainer — "make it a third-party plugin").Ten plugins, each of which declares kind: "memory" and ships today. Every cell is grounded in project docs, npm metadata, or GitHub issue threads; no hands-on testing was performed. Horizontal scroll if the table overflows.
| Plugin | Status | Slot relationship | Embeddings / Store | Bugs & maturity risks | Self‑host | Maintained |
|---|---|---|---|---|---|---|
| memory-core bundled with openclaw/openclaw | Default | Owns slot by default | OpenAI text-embedding-3-small default; auto-detects OpenAI, Gemini, Voyage, Mistral keys. SQLite + FTS5 + sqlite-vec. |
Reddit roundup rates the default Markdown path C-tier — token bloat as files grow, hit-or-miss recall on long histories. Silent pre-compaction memory-flush and optional "dreaming" consolidation included. Mature; zero external deps. | Yes | Yes first-party |
| memory-lancedb @noncelogic/memory-lancedb | Released | Replaces memory-core |
OpenAI or Gemini embeddings; LanceDB (local columnar). | Bug #7273 — openclaw status reported "unavailable" for non-core memory plugins (fixed on main). LanceDB native binaries can fail on macOS ARM. Single-tool memory_recall vs core's two-tool flow. LanceDB's own benchmark: ~76% accuracy vs core's 52%, faster average latency. |
Yes | Yes small team (3) |
| memory-lancedb-pro CortexReach/memory-lancedb-pro | Beta · v1.1.0-b10 | Replaces memory-core |
OpenAI-compatible, Jina, and others; LanceDB vector store + Jina cross-encoder reranker; hybrid vector + BM25 fusion. | Still beta. Issue #61936: dreaming doesn't fire when an external slot owner is active (fixed on main via PR #65411). LLM-driven "smart extraction" burns tokens; LanceDB's blog reports ~80% accuracy but ~14.3s average latency — nearly 2× memory-lancedb. Six-category Weibull decay model is ambitious and hard to tune. |
Yes | Yes very active |
| openclaw-honcho @honcho-ai/openclaw-honcho | Released · v1.2.2 | Replaces memory-core and memory-lancedb; non-destructively migrates legacy MEMORY.md |
Managed Honcho service (hosted or self-hosted); semantic search over "conclusions" extracted from conversations; dual-peer model (user + agent). | "Tools, not files" — migrating away from MEMORY.md can feel like a one-way door. Managed tier sends conversation text to Honcho's API. Users in Issue #60572 cite Honcho as "integration rated 3/10 due to slot exclusivity" — using it costs you memory-core's dreaming. |
Yes blank API key + custom baseUrl |
Yes Plastic Labs |
| openclaw-mem0 @mem0/openclaw-mem0 | Released · v1.0.3 | Replaces memory-core (must explicitly set plugins.slots.memory) |
Platform: Mem0 Cloud manages everything. OSS: OpenAI embeddings default; swappable vector store (memory, qdrant, chroma, etc.), swappable LLM. |
Common footgun — installing without setting the slot leaves the plugin inactive; docs clarified in PR #4546. Platform mode sends conversations to Mem0 Cloud (Reddit rates B-tier on privacy/cost). OSS default in-memory vector store is non-persistent unless swapped. Requires OpenClaw ≥ 2026.4.15. | Yes OSS mode + Ollama/LM Studio |
Yes mem0ai org |
| cognee-openclaw @cognee/cognee-openclaw | Released · v2026.2.4+ | Replaces memory-core by default; --hybrid keeps both active |
Graph-first: builds a knowledge graph of entities/relationships over memory Markdown. 14 search types incl. GRAPH_COMPLETION, CYPHER. OpenAI embeddings for vector layer. |
Cognee Cloud does not yet support updating existing data — delete/re-add required. autoMemify (post-cognify graph enrichment) is expensive. Dedicated state files needed to handle deletions. Blog claims ~93% retrieval accuracy vs ~60% for vanilla RAG — vendor-reported. |
Yes Docker cognee/cognee |
Yes Cognee team |
| memory-powermem ob-labs/openclaw-extension-powermem | Released · v0.3.0 | Replaces memory-core |
PowerMem handles embedding + storage. SQLite via CLI mode (default); OceanBase for heavier deployments. Hybrid retrieval (dense + full-text + graph) with Ebbinghaus forgetting curve. | Thin project: 24 stars, 5 forks, 2 contributors. Requires a separate Python install (pip install powermem) alongside OpenClaw — two processes to coordinate. Reddit report: "in new version can't run aggressive mode." Config is fiddly (CLI vs HTTP, absolute paths needed in some cases). |
Yes | Active but thin 2 contributors |
| openclaw-redis-agent-memory redis-developer/openclaw-redis-agent-memory | Released · v0.2.0 | Replaces memory-core |
External Redis Agent Memory Server (Docker). Server runs Redis Stack + RediSearch for vector search; OpenAI for embeddings. Multi-tenancy via namespace + optional userId. |
Two-service footprint: plugin + Redis server. extractionStrategy options (discrete/summary/preferences/custom) underdocumented. Version 0.2 signals immaturity. Much smaller community than the LanceDB / Mem0 options — no user roundups found yet. |
Yes Docker |
Yes Redis dev org |
| openclaw-memory-qdrant openclawdir listing | Released · experimental | Replaces memory-core |
Qdrant in in-memory mode. Local embeddings via Transformers.js Xenova/all-MiniLM-L6-v2 — zero-config, zero API keys. |
Major caveat documented in the plugin itself: data exists only during process runtime. Restart the gateway and memories are gone — "future versions will support persistent storage." This alone disqualifies it for most real use. | Yes fully local |
Unclear sparse release signal |
| Remnic @remnic/plugin-openclaw | Released · v9.3.24 | Thin adapter over standalone Remnic core; embedded or delegate mode. Replaces memory-core when slotted. |
OpenAI or fully local (Ollama, LM Studio) for extraction. Hybrid search BM25 + vector + reranking via QMD. Storage: plain Markdown on disk. | Recently renamed from "Engram"; some registry entries still redirect. The cross-host ambition (Claude Code, Codex CLI, Hermes all share one store) is the selling point but also a larger surface area for breakage. Documented "gateway model source" mode adds another failure axis. | Yes @remnic/server + local LLMs |
Yes frequent releases |
memory-core + LanceDB is the sensible default pair. If you don't want to think about memory, stay on memory-core. If you notice your agent forgetting on long sessions, drop in @noncelogic/memory-lancedb — the most-battle-tested slot replacement, Reddit's S-tier pick when paired with Lossless Claw on the contextEngine slot, and LanceDB's own benchmark puts it at +24 percentage points of accuracy over core.
@honcho-ai/openclaw-honcho also lives here if you specifically want cross-session user modeling over raw fact recall — first-party, self-hostable, actively maintained by Plastic Labs. @mem0/openclaw-mem0 too, specifically in OSS mode with a persistent vector store configured.
CortexReach/memory-lancedb-pro is the most interesting upgrade path — hybrid retrieval, cross-encoder rerank, smart extraction, Weibull-decay forgetting — but it's still v1.1.0-beta.x, 2–3× slower than plain memory-lancedb, and its dreaming-coexistence bug (#61936) only just got fixed on main. Try it on a staging agent, not a primary.
@cognee/cognee-openclaw is compelling for multi-agent shared memory or relational recall, but the Cognee Cloud "can't update existing data" limit plus graph-cognify cost makes it a heavier commitment. Remnic is moving fast (v9.3.24 in ~6 weeks) but you're signing up to track a project still defining its boundaries.
Native Qdrant, native pgvector, native MongoDB, first-party memory-redis, and the Multi-Slot Memory Architecture RFC — all are open issues or closed PRs. Plenty of thread enthusiasm; no shipped code. The first-party memory-redis PR was explicitly closed with "please make this a third-party plugin."
ob-labs/memory-powermem and redis-developer/openclaw-redis-agent-memory are technically released but thin — sub-v1, single-digit contributors, no community usage signals of the LanceDB / Honcho / Mem0 / Cognee tier. Released but not yet trustworthy for production. openclaw-memory-qdrant self-documents its biggest problem: no persistence across restarts. Effectively a demo.