# ragi

> Use this tool when you need to perform semantic search and document retrieval with context-aware queries. It solves problems related to information retrieval and knowledge management by indexing and searching local documents using embedding models. The tool takes in documents and queries as inputs and outputs relevant search results, ideal for use cases where local-first search and context-aware querying are required.

Canonical page: https://skillsregistry.net/skills/susutawar-ragi  
JSON: https://api.skillsregistry.net/v1/skills/susutawar-ragi

## Description

Local-first RAG indexing and semantic search MCP server. Enables document retrieval and context-aware queries using local embedding models.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-05-26

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/hjo5q2my82)
- **Repository:** <https://github.com/SusuTawar/ragi>

## 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": "susutawar-ragi"
    }
  }
}
```

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