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MemPalace

Local verbatim memory for coding agents on ChromaDB with 45 MCP tools

Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
Stars
59.5k
License
MIT
Last commit
Oct 2026
Last release
Sep 2026
Language
Python

Overview

MemPalace stores conversation history verbatim, never summarised, and retrieves it by scoped semantic search over a palace of wings (people, projects), rooms (topics) and drawers. It runs locally with Python 3.9+ and ChromaDB by default, exposes 45 MCP tools plus a CLI, mines Claude Code, Codex and Cursor transcripts via hooks, and needs no API key: 96.6% R@5 on LongMemEval without an LLM.

Who it is for: Coding-agent users who want local, inspectable, verbatim session memory

Strengths

  • Verbatim storage; nothing is summarised or paraphrased
  • 96.6% R@5 on LongMemEval with no LLM or API key; results reproducible from the repo
  • Pluggable backends: ChromaDB, sqlite, Rust-native, Milvus, Qdrant, pgvector
  • Multi-arch Docker image; auto-save hooks for Claude Code, Codex and Cursor

Weaknesses

  • First run downloads an 80 to 300 MB embedding model; Docker needs network then
  • No native Android/Termux; GPU image is x86_64-only and unpublished
  • Docker image runs as uid 1000, so bind mounts must be readable by that uid
  • README warns about impostor domains distributing malware

What it needs

  • no GPU
  • Docker + Compose
  • Models: local embeddings (MiniLM, EmbeddingGemma), OpenAI-compatible embedding endpoints, Ollama

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