Memento Vault: Local Tool for Persistent Context in Claude Code Sessions

Memento Vault addresses the issue of Claude Code forgetting context between sessions by automatically capturing and retrieving relevant information without manual maintenance.
How It Works
The tool uses hooks that plug into Claude Code's lifecycle:
- When a session ends: A hook reads the transcript, scores it, and decides what to keep. Substantial sessions get atomic notes written to a local git repo. Each note contains one idea with frontmatter including certainty scores and tags, plus wikilinks to related notes. Trivial sessions get a one-liner in a daily log.
- When a session starts: It injects a briefing showing your project's recent sessions and the most relevant vault notes for what you're about to work on.
- On every prompt: It searches your vault and surfaces matching notes before Claude processes your input.
- On every file read: It injects context about code areas you've touched before.
Technical Details
All retrieval uses local BM25 + vector search with no LLM calls. The system has 472ms average latency per prompt and costs nothing to run. Context overhead is approximately 149 input units per session. Retrieval quality scores NDCG@10 = 0.892 on LongMemEval (500 questions).
A background consolidation layer called Inception clusters notes by embedding similarity and writes pattern notes after sessions, identifying recurring issues across projects.
The entire system uses markdown files in a git repo, browsable in Obsidian, searchable with grep, and diffable with git log. There's no database, Docker, or cloud dependency.
Installation
git clone https://github.com/sandsower/memento-vault.git
cd memento-vault
./install.sh --experimentalRequirements: Python 3 and Claude Code. QMD adds semantic search (optional). Works on Linux and macOS.
The project includes 271 tests and is MIT licensed.
📖 Read the full source: r/ClaudeAI
👀 See Also

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