memory-lancedb-pro

memory-lancedb-pro is an OpenClaw plugin that provides long-term “memory” storage and hybrid retrieval on top of LanceDB. It combines vector (ANN) search with BM25 full-text search, fuses results, applies cross-encoder reranking, and runs a multi-stage scoring pipeline including recency/importance/length normalization/time decay plus diversity (MMR). It also supports multi-scope isolation, auto-capture/auto-recall hooks in the OpenClaw lifecycle, optional Markdown mirroring, long-context embedding chunking, and a management CLI for memory CRUD/migration/reindexing.

Evaluated Mar 29, 2026 (0d ago)
Homepage ↗ Repo ↗ Ai Ml openclaw openclaw-plugin lancedb memory hybrid-retrieval bm25 vector-search cross-encoder-rerank reranking mmr multi-scope cli typescript rag
⚙ Agent Friendliness
70
/ 100
Can an agent use this?
🔒 Security
59
/ 100
Is it safe for agents?
⚡ Reliability
36
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
70
Error Messages
80
Auth Simplicity
70
Rate Limits
55

🔒 Security

TLS Enforcement
60
Auth Strength
55
Scope Granularity
70
Dep. Hygiene
55
Secret Handling
55

Strengths: multi-scope isolation is explicitly described (global, agent:<id>, custom, project, user). Security posture around transport and secrets is not fully evidenced in the provided content; embedding provider calls likely use HTTPS but TLS enforcement is not documented here. Secret handling practices (e.g., logging/never logging) are not verifiable from the snippet. Dependency hygiene cannot be assessed from the provided manifest beyond presence of common libs.

⚡ Reliability

Uptime/SLA
0
Version Stability
40
Breaking Changes
30
Error Recovery
75
AF Security Reliability

Best When

Used as an OpenClaw plugin in a TypeScript/Node environment where agents can call the plugin’s tools/hooks and where LanceDB + an embedding provider (OpenAI-compatible) are acceptable.

Avoid When

Avoid if you cannot run the plugin inside OpenClaw’s plugin lifecycle or if you require a standardized external API (REST/GraphQL/GRPC) with OpenAPI/SDK contracts; also avoid if you need strict compliance guarantees that are not documented (e.g., data residency/compliance).

Use Cases

  • RAG systems needing long-term memory with both semantic and keyword recall
  • Agentic assistants that must retrieve relevant prior facts/preferences across sessions
  • Projects that want hybrid retrieval with reranking and recency/decay weighting
  • Multi-tenant or multi-agent environments requiring scoped memory isolation
  • Teams that need memory management operations (import/export, migrate, reembed) via CLI

Not For

  • Production deployments that require a network-accessible REST/GraphQL service API from this package alone
  • Use cases needing fine-grained, per-record user authorization enforced externally (the plugin appears to implement logical scoping inside OpenClaw, not cryptographic enforcement)
  • Organizations that cannot store any memory content locally/offline (LanceDB storage plus optional Markdown mirror)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
No
Webhooks
No

Authentication

Methods: OpenAI-compatible embedding provider API key / auth configuration (implied by OpenAI dependency and OpenAI-compatible wording)
OAuth: No Scopes: No

Authentication is primarily to external embedding/reranker endpoints (OpenAI-compatible and “compatible endpoint” mentions). The README focuses on configuration behavior rather than a formal auth method list (e.g., API key vs bearer token) or per-scope authorization with the external endpoints.

Pricing

Free tier: No
Requires CC: No

Pricing for the plugin itself is not described; costs depend on the embedding/reranking providers used (not specified here).

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Documented

Known Gotchas

  • This is a plugin integrated into OpenClaw lifecycle hooks; an external agent expecting a standalone HTTP API will not find one.
  • Cross-encoder reranking depends on an external compatible endpoint; behavior includes fallback on API failure, so results may vary.
  • Hybrid scoring and diversity thresholds (minScore, MMR demotion threshold, age half-lives) can materially change recall; agents should be configured/tuned rather than assuming stable ranking.
  • Memory management CLI exists, but whether tool calls are strictly idempotent for repeated operations is not documented in the provided content.

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Scores are editorial opinions as of 2026-03-29.

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