Open Source AI Memory Storage for NodeJS Projects

What Mind Palace Does
Mind Palace is an open source memory storage and retrieval system built for NodeJS projects. It addresses the need to share and persist information across LLM chat sessions and other LLM feature interactions.
Key Features and Implementation
The system works by ingesting and automatically extracting "memories" from LLM interactions. These memories are summarized single bits of information that get vectorized for storage.
When you need to provide relevant context back to an LLM (before a new chat session starts or after user requests), you pass conversation context to the recall method. An LLM then searches the vector store and returns only the most relevant memories.
This approach prevents context size issues as history and memory count grows while ensuring the LLM always has access to important context.
Built-in Support and Development
- Supports major LLMs: GPT, Gemini, and Claude
- Integrates with major vector store providers: Weaviate and Pinecone
- Includes a developer UI sandbox for testing
- Features a deduping system and configurable components
- Unit tests were coded using Claude Opus
The creator designed it with low barrier to use in mind, making it easy to integrate into existing NodeJS projects.
📖 Read the full source: r/ClaudeAI
👀 See Also

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A developer built a persistent memory layer for Claude using local vector search (Qdrant + Qwen3) and MCP integration, achieving 82% token reduction, 39ms hot-path retrieval, and session crystallization via L4 nodes.
OpenClaw AI Agent with 6 Roles, Memory, and ADHD-Aware Design: Daily Ops Breakdown
A solo founder with ADHD built an open-source AI agent with 6 roles (action planner, debriefer, writer, legal, investigator, CRM) sharing memory, auto-generating follow-ups and drafts from transcripts.