# ragora

> ragora — mregmi-ragora. Use this tool when you need to discover, search, and synthesize answers from large knowledge bases, solving problems related to information retrieval and data analysis. It takes in queries and parameters as inputs and returns relevant answers and insights as outputs through its REST API interface. Ideal for use cases where complex data needs to be searched, filtered, and synthesized into actionable information.

Canonical page: https://skillsregistry.net/skills/mregmi-ragora  
JSON: https://api.skillsregistry.net/v1/skills/mregmi-ragora

## Description

Use Ragora MCP tools and REST API to discover, search, and synthesize answers from knowledge bases.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/mregmi-ragora)

## 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": "mregmi-ragora"
    }
  }
}
```

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