LongMemory
LongMemory: local-first memory for AI agents with temporal truth, provenance, and hybrid recall
Memory-LanceDB-Pro gives OpenClaw agents hybrid search, smart extraction, and intelligent forgetting
memory-lancedb-pro is an open-source ai agents project by CortexReach (CortexReach/memory-lancedb-pro on GitHub). It has 4,454 GitHub stars and 729 forks, is released under the MIT license, and was last updated on GitHub on 8 October 2026.
Memory-LanceDB-Pro is a plugin for the OpenClaw agent runtime, so have a working OpenClaw setup.
Install memory-lancedb-pro (beta channel) via the OpenClaw plugin command or npm.
Set it as the memory slot in openclaw.json, choose an embedding provider, and validate the config.
Restart the gateway and hold a conversation — facts are captured and recalled automatically.
Conversations are distilled into six memory categories automatically, not stored as raw transcripts.
Vector search plus BM25 keyword search, re-ranked by a cross-encoder for precision.
Memories are separated per agent, user, or project to prevent cross-contamination.
A Weibull decay model ages memories so stale facts fade like human memory.
Your MEMORY.md and memory files are indexed and searchable alongside captured facts.
Backup, export, import, upgrade, and re-embed commands keep the memory store maintainable.
Clone the project and enter its directory (most users install the plugin directly, next step).
git clone https://github.com/CortexReach/memory-lancedb-pro.git
cd memory-lancedb-proInstall into OpenClaw from the beta channel (or `npm i memory-lancedb-pro@beta`).
openclaw plugins install memory-lancedb-pro@betaPoint OpenClaw's memory slot at the plugin in openclaw.json, validate, and restart the gateway.
openclaw config validate
openclaw gateway restartCortexReach develops the plugin for the OpenClaw ecosystem.
The plugin's README badge states the MIT license. You supply an embedding provider — local Ollama embeddings can avoid API costs.
Only if you pick a hosted embedding provider (OpenAI, Jina, Gemini); Ollama or a local OpenAI-compatible endpoint works without one.
The plugin adds LLM-based extraction, hybrid vector+BM25 retrieval with reranking, multi-scope isolation, and decay-based forgetting beyond basic storage.
Run `openclaw plugins install memory-lancedb-pro@beta`, set the memory slot and embedding provider in openclaw.json, then `openclaw gateway restart`.
LongMemory: local-first memory for AI agents with temporal truth, provenance, and hybrid recall
Open-source AI memory that gives agents persistent long-term recall.
Self-evolving memory OS for LLMs and agents: persistent graph memory, hybrid retrieval, skill reuse.
The memory API that gives AI apps instant, lasting context.
Simple desktop AI assistant with knowledge bases, agents, and web search.
Stateful AI agents with memory that learns and improves.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if memory-lancedb-pro is not the right fit.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Free and open — grab the source, star the repo, and start creating.