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io.github.rog0x/cache

Official registry AI and agents

Cache headers, CDN, LRU simulation for AI agents

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package @rog0x/mcp-cache-tools
Claude Code 
claude mcp add cache -- npx -y @rog0x/mcp-cache-tools@1.0.2
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "cache": {
            "command": "npx",
            "args": [
                "-y",
                "@rog0x/mcp-cache-tools@1.0.2"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. @rog0x/mcp-cache-tools
  2. Tools
  3. Setup
  4. MCP Configuration
  5. License

@rog0x/mcp-cache-tools

MCP Server #30 — Caching and memoization tools for AI agents.

Analyze, generate, simulate, and optimize caching strategies across HTTP, CDN, and browser layers.

Tools

1. analyze_cache_headers

Analyze HTTP cache headers (Cache-Control, ETag, Last-Modified, Expires, Vary). Grades the overall caching strategy A+ through F and provides actionable improvement suggestions with context-aware advice for static assets, API responses, HTML pages, and media.

2. generate_cache_key

Generate deterministic cache keys from various inputs:

  • URL mode — normalizes URL, sorts query params, filters include/exclude params
  • Body mode — hashes request body with JSON key sorting for consistency
  • Composite mode — combines multiple key parts into a single deterministic hash

Supports namespacing, versioning, TTL, and outputs ready-to-use Redis/Memcached commands.

3. simulate_cache

Simulate cache behavior for a sequence of requests. Compare eviction strategies side-by-side:

  • LRU — Least Recently Used
  • LFU — Least Frequently Used
  • FIFO — First In, First Out
  • TTL — Time-To-Live based expiration

Outputs hit rate, miss rate, eviction count, and step-by-step timeline.

4. check_cdn_headers

Detect which CDN is serving a resource from response headers. Identifies Cloudflare, Fastly, Akamai, CloudFront, Vercel, Netlify, Google Cloud CDN, Azure CDN, KeyCDN, and Bunny CDN. Reports cache status (HIT/MISS/STALE/BYPASS), edge server, and POP location.

5. analyze_browser_cache

Analyze what resources a page would cache in the browser. Determines cache type (strong, heuristic, conditional, none), duration, revalidation strategy, and estimates bandwidth/time savings on repeat visits. Groups results by resource type with optimization suggestions.

Setup

npm install
npm run build

MCP Configuration

{
  "mcpServers": {
    "mcp-cache-tools": {
      "command": "node",
      "args": ["D:/products/mcp-servers/mcp-cache-tools/dist/index.js"]
    }
  }
}

License

MIT

Frequently asked questions

What is io.github.rog0x/cache?

Cache headers, CDN, LRU simulation for AI agents

How do I install io.github.rog0x/cache?

It runs on your machine. In Claude Code: claude mcp add cache -- npx -y @rog0x/mcp-cache-tools@1.0.2. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.rog0x/cache need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.rog0x/cache open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains io.github.rog0x/cache?

It is published by rog0x. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.