nocturne_memory
Agents retain context across sessions without vector search latency or semantic drift.
A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, session, or tool. Drop-in replacement for OpenClaw.
- Multi-session customer support agents tracking issue history and resolution patterns
- Code assistants remembering project structure and past refactoring decisions
- Workflow orchestration that maintains task dependencies across agent invocations
Agents retain context across sessions without vector search latency or semantic drift. Persistent memory reduces redundant context-building and improves decision consistency in long-running workflows.
Teams deploying multi-turn MCP agents that need reliable state management and audit trails across conversations or integrations.
https://github.com/Dataojitori/nocturne_memory
By Dataojitori
How to Get It
claude plugins install Dataojitori/nocturne_memory
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:
Help me multi-session customer support agents tracking issue history and resolution patterns
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Reddit
- One of Nocturne's artists has posted young Emanuel on twitter. Sneak peak of som — Reddit · 749 pts
- Was looking for nocturnals shine and placed a markar on the map from memory and — Reddit · 623 pts
- The 2020 Cookeville EF4 might be one of the most overlooked yet one of the most — Reddit · 205 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 1,119 GitHub stars; contributors unknown; last commit 1d 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): 1,119 GitHub stars; contributors unknown; last commit 1d ago; license MIT.