広告掲載
MCP.so
ログイン

Memory Quality MCP Server

@ladyiceberg

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

作者

ladyiceberg

投稿者

ladyiceberg z

Memory Quality MCP Server について

A Claude Code MCP plugin that audits and cleans up your AI memory.

#memory#mcp#claude#claude-code

Memory Quality MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "memory-quality": {
      "command": "uvx",
      "args": [
        "memory-quality-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-key-here"
      }
    }
  }
}

Memory Quality MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Memory Quality Mcp?

Memory Quality Mcp audits and cleans up Claude Code’s auto-saved memories. It provides a health check with four tools that scan, score, clean, and visualize your memory store. It supports multiple LLM providers and auto-detects language from system locale.

How to use Memory Quality Mcp?

Invoke the provided tools (memory_audit(), memory_report(), memory_cleanup(), memory_dashboard()) after installation. A demo mode is available that requires no real memory files.

Key features of Memory Quality Mcp

  • Instant memory scan with no LLM cost (memory_audit())
  • Four-dimension scoring: Importance, Recency, Credibility, Accuracy
  • Conflict detection and safe cleanup with dry-run preview
  • Auto-backup of cleaned memories to .trash/ folder
  • Visual health dashboard with scores and recommendations
  • Supports OpenAI, Anthropic, Kimi, and MiniMax providers

Use cases of Memory Quality Mcp

  • Audit a bloated memory store for stale or junk entries
  • Identify conflicting preferences saved over many sessions
  • Clean up one-off remarks that were over-interpreted as facts
  • Generate a health report to understand memory quality at a glance

よくある質問

1

What does Memory Quality Mcp do?

It scans and cleans up the automatic memories that Claude Code saves from conversations, helping you remove stale, conflicting, or junk entries.

2

Do I need real memory files to try it?

No. You can use demo mode first—no real memory files are required.

3

What tools are available?

Four tools: `memory_audit()` (instant scan), `memory_report()` (scoring + conflict detection), `memory_cleanup()` (safe cleanup with backup), and `memory_dashboard()` (visual health dashboard).

4

Which LLM providers are supported?

OpenAI, Anthropic, Kimi, and MiniMax are explicitly mentioned.

5

Is the cleanup operation safe?

Yes. It offers a dry-run preview and automatically backs up memories to a `.trash/` folder before performing any cleanup.

コメント

「メモリとナレッジ」の他のコンテンツ

Agimem

Persistent memory for AI agents. Hosted MCP server with capsule-scoped key/value storage, tags, TTL expiration, bulk ops, and RBAC.

Orcha

westonhancock

Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age

OpenLore

aakarim

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, and pipes against a virtual filesystem backed by your documentation. Identity-scoped access, governed writing with human approval, and portab

66

Neither MCP

stonianua

Project context your AI can query through MCP — with source evidence.

ctxfile

ctxfile

Local-first MCP server that snapshots your project's working state into one context object. Open-core, privacy-first.

2
広告掲載