Mnemosyne Cache MCP

Mnemosyne Cache MCP

High-performance MCP response caching server that reduces latency from ~3000ms to ~0.001ms for repeated tool calls using a dual-layer SQLite and LRU memory cache.

Category
Visit Server

README

Mnemosyne Cache MCP

High-performance MCP (Model Context Protocol) response caching server. Reduces latency from ~3000ms to ~0.001ms for repeated tool calls.

Overview

The Mnemosyne Cache MCP server provides transparent caching for MCP tool responses using a dual-layer architecture:

  • SQLite: Persistent storage backend
  • LRU Memory Cache: Hot entry acceleration

Key Features

  • Intelligent TTL Management: Server-specific expiration policies
  • Write-Operation Detection: Automatically skips caching for mutations
  • SHA256 Cache Keys: Deterministic key generation from tool calls
  • Statistics Tracking: Hits, misses, evictions, and hit rate monitoring
  • Zero Configuration: Sensible defaults with environment variable overrides

Performance Impact

Uncached serena tool call:    ~3000ms
Cached serena tool call:       ~0.001ms
Performance improvement:       3,000,000% faster

Installation

npm install -g @zhadyz/mnemosyne-cache-mcp

Or use with npx:

npx @zhadyz/mnemosyne-cache-mcp

Configuration

Environment Variables

# Database location (default: ./mcp_cache.db)
export MNEMOSYNE_CACHE_DB="/path/to/cache.db"

# Memory cache settings (default: enabled, 1000 entries)
export MEMORY_CACHE="true"
export MEMORY_CACHE_SIZE="1000"

Default TTL Values

Server TTL (seconds) Rationale
serena 1800 (30 min) Code changes frequently
context7 7200 (2 hours) Docs are stable
github 600 (10 min) Repos change
filesystem 300 (5 min) Files change
memory 0 (never) Mutable state
mnemosyne 0 (never) Mutable state

MCP Configuration

Add to your Claude Code MCP settings (.claude/mcp.json):

{
  "mcpServers": {
    "mnemosyne-cache": {
      "command": "npx",
      "args": ["@zhadyz/mnemosyne-cache-mcp"],
      "env": {
        "MNEMOSYNE_CACHE_DB": "./.cache/mcp_cache.db",
        "MEMORY_CACHE": "true",
        "MEMORY_CACHE_SIZE": "1000"
      }
    }
  }
}

Or with local installation:

{
  "mcpServers": {
    "mnemosyne-cache": {
      "command": "node",
      "args": ["/path/to/mnemosyne-cache-mcp/dist/index.js"]
    }
  }
}

Available Tools

cache_get

Retrieve a cached MCP tool response.

{
  "server_name": "serena",
  "tool_name": "find_symbol",
  "args": {
    "name_path": "MyClass",
    "relative_path": "src/main.ts"
  }
}

Response:

{
  "cached": true,
  "data": { /* tool response */ }
}

cache_set

Store an MCP tool response with automatic TTL.

{
  "server_name": "serena",
  "tool_name": "find_symbol",
  "args": { /* tool arguments */ },
  "response": { /* tool response */ }
}

Response:

{
  "success": true,
  "message": "Cached response for serena:find_symbol"
}

cache_invalidate

Invalidate cache entries by server or tool.

{
  "server_name": "github",
  "tool_name": "get_issue"  // optional
}

Response:

{
  "success": true,
  "invalidated_entries": 42
}

cache_stats

Get cache performance statistics.

{}

Response:

{
  "hits": 1523,
  "misses": 287,
  "evictions": 12,
  "totalEntries": 1810,
  "totalSizeBytes": 15728640,
  "sizeMB": 15.0,
  "hitRate": 84.14,
  "avgHitTimeMs": 0.001,
  "avgMissTimeMs": 3127.5
}

Cache Key Generation

Cache keys are deterministically generated using SHA256:

const keyMaterial = `${serverName}:${toolName}:${sortedArgs}`;
const cacheKey = sha256(keyMaterial);

Arguments are JSON-stringified with sorted keys to ensure identical calls produce identical keys regardless of argument order.

Write Operation Detection

The following verbs in tool names are automatically excluded from caching:

  • create
  • update
  • delete
  • remove
  • modify
  • write

Examples of non-cacheable operations:

  • github__create_issue
  • filesystem__write_file
  • serena__replace_symbol_body

Architecture

┌─────────────────────────────────────────┐
│         MCP Client (Claude Code)        │
└────────────────┬────────────────────────┘
                 │
                 │ stdio transport
                 ▼
┌─────────────────────────────────────────┐
│      Mnemosyne Cache MCP Server         │
│                                         │
│  ┌───────────────────────────────────┐ │
│  │     LRU Memory Cache (Hot)        │ │
│  │     - 1000 entries (default)      │ │
│  │     - O(1) lookup                 │ │
│  └───────────┬───────────────────────┘ │
│              │ miss                    │
│              ▼                          │
│  ┌───────────────────────────────────┐ │
│  │     SQLite Database (Cold)        │ │
│  │     - Persistent storage          │ │
│  │     - TTL expiration              │ │
│  └───────────────────────────────────┘ │
│                                         │
│  Cache Key: SHA256(server:tool:args)   │
└─────────────────────────────────────────┘

Development

Build

npm install
npm run build

Local Testing

node dist/index.js

Send MCP protocol messages via stdin:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list",
  "params": {}
}

License

MIT

Author

ZHADYZ - MENDICANT_BIAS DevOps Agent

Part of the MENDICANT autonomous AI orchestration system.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured