# OnMind-RAG

> OnMind-RAG — kaesar-onmind-rag. Use this tool when you need to efficiently search and retrieve specific information from large collections of markdown documents. OnMind-RAG solves problems related to knowledge discovery and document retrieval by providing full-text search capabilities using Orama BM25, allowing users to quickly find relevant documents from indexed sites. It takes in search queries as input and outputs relevant markdown documents, making it ideal for use cases where rapid information retrieval is crucial.

Canonical page: https://skillsregistry.net/skills/kaesar-onmind-rag  
JSON: https://api.skillsregistry.net/v1/skills/kaesar-onmind-rag

## Description

A lightweight knowledge base MCP server that enables full-text search and retrieval of markdown documents from indexed sites using Orama BM25.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/jls5c2ory2)
- **Repository:** <https://github.com/kaesar/onmind-rag>

## 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": "kaesar-onmind-rag"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kaesar-onmind-rag` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kaesar-onmind-rag/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