Local-first AI memory. Verbatim storage, pluggable backend, 96.6% R@5 raw on LongMemEval — zero API calls.

CautionBeware of impostor sites. MemPalace has no other official websites. The only official sources are this GitHub repository, the PyPI package, and the docs at mempalaceofficial.com. Any other domain (including .tech, .net, or other .com variants) is an impostor and may distribute malware. Details and timeline: docs/HISTORY.md.

What it is MemPalace stores your conversation history as verbatim text and retrieves it with semantic search. It does not summarize, extract, or paraphrase. The index is structured — people and projects become wings, topics become rooms, and original content lives in drawers — so searches can be scoped rather than run against a flat corpus. The retrieval layer is pluggable. The current default is ChromaDB; the interface is defined in mempalace/backends/base.py and alternative backends can be dropped in without touching the rest of the system. Nothing leaves your machine unless you opt in. Architecture, concepts, and mining flows: mempalaceofficial.com/concepts/the-palace.

Install MemPalace ships a CLI, so install it in an isolated environment to avoid PEP 668 errors on Debian/Ubuntu/Homebrew Pythons and to keep mempalace's deps (chromadb, numpy, grpcio, …) from conflicting with anything else in your global site-packages. We recommend uv — uv tool install puts the mempalace CLI in an isolated environment on your PATH: uv tool install mempalace mempalace init ~/projects/myapp pipx works the same way if you prefer it: pipx install mempalace. Prefer plain pip only inside an activated virtualenv where you explicitly want import mempalace available: python -m venv .venv && source .venv/bin/activate pip install mempalace Docker A container image is also available for running the MCP server or the CLI without a local Python toolchain. Everything persists under /data (palace, config, and the cached embedding model), so mount a volume there.