advanced-memory-mcp

Advanced Memory (Memops)

📖 Installation Guide — quick start, manual setup, and troubleshooting

• Why — Give an MCP-capable assistant a durable place for notes, research, and retrieval: search and RAG over your content instead of losing context every session.
• What — A FastMCP 3.2 GA server (Python 3.12+) exposing 79 tools across 12 Industrial Portmanteaus (audio, inbox, skills, zettel, nav, notes, search, knowledge, project, system, mcp, typora). Optimized with 2026 Industrial Docstrings (Rationale-First) and Discriminated Unions for high-fidelity tool selection in Antigravity/Cursor.
• How — Connect the MCP server from your client (installation, then usage). Optionally run the webapp for a browser UI on top of the same backend.

Quick Start

git clone https://github.com/sandraschi/advanced-memory-mcp
cd advanced-memory-mcp
just

This opens an interactive dashboard showing all available commands. Run just bootstrap to install dependencies, then just serve or just dev to start.

Manual Setup

If you don't have just installed:

Documentation

• Installation — Python uv, optional OCR/Pandoc
• Usage — MCP clients, webapp, advanced topics
• AI features — RAG, agentic mode, sampling
• FastMCP 3.2 — Managed Namespaces, prefabs, CodeMode, transports
• Product requirements (PRD) — current mission, scope, KPIs (1.8.x)
• Architecture
• Fleet / multi-node
• Compliance & standards
• Development — just recipes (lint, test, pack)
• Changelog
• Release checklist (MCPB + Git tag)

日本語 (Japanese)

Advanced Memory (Memops) は、AIコーディングエージェントのための永続的な知識グラフ＆Zettelkastenメモリシステムです。セッションをまたいで知識を保持し、検索・RAG・ノート・スキル管理・音声操作などを提供します。

• 12のポートマントーツール、79の操作 — adn_search（全文検索＋RAG）、adn_notes（ノートCRUD）、adn_zettel（Zettelkasten生成・分析）、adn_skills（スキル管理）、adn_audio（音声認識・合成）など
• デュアルトランスポート — stdio（Claude Desktop / Cursor）＋ HTTP/SSE（Webダッシュボード）
• ローカルファースト — SQLite + LanceDBベクトル検索、外部API不要
• Claude Codeフック対応 — セッション開始時に自動リコール（.claude-plugin/）

📖 クイックスタート: git clone → just bootstrap → just serve

日本語での詳細ドキュメントは docs/ja/ をご覧ください。

Author: Sandra Schipal · Vienna, Austria

🛡️ Industrial Quality Stack

This project adheres to SOTA 14.1 industrial standards for high-fidelity agentic orchestration:

• Python (Core): Ruff for linting and formatting. Zero-tolerance for print statements in core handlers (T201).
• Webapp (UI): Biome for sub-millisecond linting. Strict noConsoleLog enforcement.
• Protocol Compliance: Hardened stdout/stderr isolation to ensure crash-resistant JSON-RPC communication.
• Automation: Justfile recipes for all fleet operations (just lint, just fix, just dev).
• Security: Automated audits via bandit and safety.