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Memory Cache Server MCP Server

@MCP-Mirror

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

MCP-Mirror

Memory Cache Server MCP Server について

Mirror of

#memory-cache#mcp-server#token-reduction

Memory Cache Server 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-cache": {
      "command": "node",
      "args": [
        "/path/to/ib-mcp-cache-server/build/index.js"
      ]
    }
  }
}

Memory Cache Server 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。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Memory Cache Server?

Memory Cache Server is a Model Context Protocol (MCP) server that reduces token consumption by automatically caching data between language model interactions. It works with any MCP client and any language model that uses tokens.

How to use Memory Cache Server?

Install by cloning the repository, running npm install and npm run build. Add the server to your MCP client settings using the command "node" and args pointing to build/index.js. The server starts automatically with your client and caches data without further action.

Key features of Memory Cache Server

  • Automatic caching of data between interactions
  • Configurable maximum cache entries (default 1000)
  • Configurable maximum memory usage (default 100MB)
  • Time-to-live (TTL) for cached items (default 1 hour)
  • Configurable cleanup and stats update intervals
  • Monitor cache effectiveness through hit/miss statistics

Use cases of Memory Cache Server

  • Repeated file reading: cache file content to avoid re-sending tokens
  • Repeated computations: cache results of analysis or calculations
  • Frequent data access: serve cached data for the same queries until TTL expires
  • Project navigation: cache directory listings and file contents

よくある質問

1

What data does the cache store?

The cache stores file content, computation results, and any frequently accessed data that would otherwise need to be re-sent.

2

How does it reduce token consumption?

By storing data when first encountered and serving it from cache on subsequent requests, avoiding the need to re-transmit the same information.

3

Does it work with any language model?

Yes, it works with any language model that uses tokens, as long as you connect through an MCP client.

4

How do I configure the cache?

You can set `maxEntries`, `maxMemory`, `defaultTTL`, `checkInterval`, and `statsInterval` via `config.json` or environment variables (`MAX_ENTRIES`, `MAX_MEMORY`, etc.).

5

How can I verify the cache is working?

Look for faster responses on repeated operations, consistent answers about unchanged content, and no need to re-read files. The server prints "Memory Cache MCP server running on stdio" when started.

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