AI memory system — mine projects and conversations into a searchable palace. 19 MCP tools, auto-save hooks, guided setup.
Search your memories across the MemPalace using semantic search with wing/room filtering.
Show the current state of your memory palace — wings, rooms, drawer counts, and suggestions.
Show comprehensive MemPalace help — available skills, MCP tools, CLI commands, hooks, and architecture.
Set up MemPalace — install the package, initialize a palace, configure MCP server, and verify everything works.
Mine projects and conversations into the MemPalace. Supports project files, conversation exports, and auto-classification.
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Every conversation you have with an AI — every decision, every debugging session, every architecture debate — disappears when the session ends. Six months of work, gone. You start over every time.
Other memory systems try to fix this by letting AI decide what's worth remembering. It extracts "user prefers Postgres" and throws away the conversation where you explained why. MemPalace takes a different approach: store everything, then make it findable.
The Palace — Ancient Greek orators memorized entire speeches by placing ideas in rooms of an imaginary building. Walk through the building, find the idea. MemPalace applies the same principle to AI memory: your conversations are organized into wings (people and projects), halls (types of memory), and rooms (specific ideas). No AI decides what matters — you keep every word, and the structure gives you a navigable map instead of a flat search index.
Raw verbatim storage — MemPalace stores your actual exchanges in ChromaDB without summarization or extraction. The 96.6% LongMemEval result comes from this raw mode. We don't burn an LLM to decide what's "worth remembering" — we keep everything and let semantic search find it.
AAAK (experimental) — A lossy abbreviation dialect for packing repeated entities into fewer tokens at scale. Readable by any LLM that reads text — Claude, GPT, Gemini, Llama, Mistral — no decoder needed. AAAK is a separate compression layer, not the storage default, and on the LongMemEval benchmark it currently regresses vs raw mode (84.2% vs 96.6%). We're iterating. See the note above for the honest status.
Local, open, adaptable — MemPalace runs entirely on your machine, on any data you have locally, without using any external API or services. It has been tested on conversations — but it can be adapted for different types of datastores. This is why we're open-sourcing it.
[![][version-shield]][release-link] [![][python-shield]][python-link] [![][license-shield]][license-link] [![][discord-shield]][discord-link]
Quick Start · The Palace · AAAK Dialect · Benchmarks · MCP Tools
| 96.6% LongMemEval R@5 raw mode, zero API calls | 500/500 questions tested independently reproduced | $0 No subscription No cloud. Local only. |
Reproducible — runners in benchmarks/. Full results. The 96.6% is from raw verbatim mode, not AAAK or rooms mode (those score lower — see note above).
npx claudepluginhub p/amirulandalib-mempalace-claude-pluginUltra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.
Give your AI a memory — mine projects and conversations into a searchable palace. 19 MCP tools, auto-save hooks, and guided setup.
Claude harness - A harness for solo developers (Vibecoders) to handle full-cycle contract development.
Code intelligence powered by a knowledge graph. Provides execution flow tracing, blast radius analysis, and augmented search across your codebase.
No description provided.
Harness-native ECC operator layer - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Evidence-gated AI coding workflow: scan → analyze → plan → TDD → execute → fix → verify → review, powered by Codebase Memory MCP >= 0.9.0 with optional Serena LSP intelligence. Includes blast-radius planning, test/cycle gates, independent review, and Windows Git Bash hook auto-resolution.
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Reliable automation, in-depth debugging, and performance analysis in Chrome using Chrome DevTools and Puppeteer