memem
Enables Claude to retain institutional knowledge across conversations, reducing redundant analysis and accelerating decision-making by building searchable ar…
A Claude Code plugin that gives Claude persistent memory across sessions — stores lessons and decisions as markdown in your Obsidian vault, searches them with SQLite FTS5, and mines past transcripts automatically.
- Ask Claude to recall previous project decisions and architectural patterns from past sessions.
- Generate a searchable knowledge base of lessons learned across multiple data analysis projects.
- Automate extraction of key insights from conversation transcripts into organized notes.
Enables Claude to retain institutional knowledge across conversations, reducing redundant analysis and accelerating decision-making by building searchable archives of past insights and patterns.
Data analytics teams and consultants leveraging Claude iteratively who need continuous learning and decision provenance across multiple projects.
https://github.com/TT-Wang/memem
By TT-Wang
How to Get It
claude plugins install TT-Wang/memem
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Recall previous project decisions and architectural patterns from past sessions
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 0d ago; license MIT.