# echocache

> echocache — kskurtveit-echocache. Use this tool when you need to optimize expensive large language model (LLM) queries by caching results, reducing redundant computations and improving response times. The echocache MCP server utilizes HTTP-style freshness and semantic recall to provide related answers, making it ideal for applications with frequent or similar queries. It accepts LLM queries as input and returns cached results, streamlining the development process with git integration.

Canonical page: https://skillsregistry.net/skills/kskurtveit-echocache  
JSON: https://api.skillsregistry.net/v1/skills/kskurtveit-echocache

## Description

MCP server that caches expensive LLM results — HTTP-style freshness plus semantic recall of related answers

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/kskurtveit/echocache)

## 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": "kskurtveit-echocache"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kskurtveit-echocache` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kskurtveit-echocache/pull`

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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