MemPalace

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GitHub Python MIT

Description

MemPalace is an open-source AI memory system providing a persistent long-term memory layer for AI agents, with ChromaDB vector storage and MCP protocol integration.

Key Features

  • Verbatim storage & semantic search — conversation history stored as-is, retrieved via semantic search without summarization or paraphrasing
  • Palace-style indexing — organizes memory as Wings (people/projects) → Rooms (topics) → Drawers (verbatim content)
  • Local-first zero API — core retrieval requires no API key, cloud, or LLM, uses ChromaDB as default local vector store
  • Pluggable retrieval backend — swappable via base.py interface to support alternative vector databases
  • Knowledge graph — temporal entity-relationship graph with validity windows, supporting add/query/invalidate/timeline
  • MCP Server — 29 MCP tools covering palace read/write, knowledge-graph operations, and agent diaries

Use Cases

💡 Providing persistent long-term memory for Claude Code and other AI coding assistants across sessions
💡 Storing and retrieving large conversation histories locally to protect data privacy
💡 Tracking project stakeholder relationships and decision timelines via knowledge graph
💡 Integrating memory systems into AI agent workflows through MCP tools
💡 Validating memory retrieval performance on LongMemEval and other benchmarks

Tags

memory long-term-memory chromadb mcp python

Categories

🧩 Agent Memory

Quick Start

uv tool install mempalace
mempalace init ~/projects/myapp
# Mine project file content
mempalace mine ~/projects/myapp
# Search memories
mempalace search 'why did we switch to GraphQL'
# Load context for new session
mempalace wake-up
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