# io.github.rog0x/cache

> Use this tool when you need to optimize data retrieval and reduce latency for AI agents by simulating cache headers, Content Delivery Networks (CDNs), and Least Recently Used (LRU) cache mechanisms. It solves problems related to slow data access, high network traffic, and inefficient resource utilization. This tool takes in cache configuration and data requests as inputs and outputs optimized cache responses, making it ideal for use cases involving frequent data queries and limited network resources.

Canonical page: https://skillsregistry.net/skills/io-github-rog0x-cache  
JSON: https://api.skillsregistry.net/v1/skills/io-github-rog0x-cache

## Description

Cache headers, CDN, LRU simulation for AI agents

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.rog0x%2Fcache)
- **Repository:** <https://github.com/rog0x/mcp-cache-tools>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "io-github-rog0x-cache"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-rog0x-cache` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-rog0x-cache/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt