# RAMen

> RAMen — rohit-dnath-ramen. Use this tool when you need to accelerate AI applications with a fast in-memory data store that supports native vector search and semantic caching. RAMen solves problems related to slow data retrieval and processing in AI systems, providing a drop-in Redis protocol for seamless integration. It is ideal for use cases where high-performance data storage and retrieval are critical, with a simple interface that includes a built-in MCP server for agents.

Canonical page: https://skillsregistry.net/skills/rohit-dnath-ramen  
JSON: https://api.skillsregistry.net/v1/skills/rohit-dnath-ramen

## Description

RAMen is a fast in-memory data store like Redis, but built for AI: drop-in Redis protocol, native vector search, semantic caching, and a built-in MCP server for agents. Single Go binary, BSD-3.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** BSD-3-Clause
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Rohit-Dnath/RAMen)

## 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": "rohit-dnath-ramen"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rohit-dnath-ramen` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rohit-dnath-ramen/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