# raggy-mcp

> Use this tool when you need to enable AI agents to retain knowledge and memories across sessions, solving problems of decision recall, error tracking, and preference persistence. It provides a centralized, persistent memory and knowledge graph, allowing agents to learn from past experiences and adapt to new situations. Ideal for use cases requiring continuous learning, error analysis, and personalized interactions.

Canonical page: https://skillsregistry.net/skills/sonofakel-raggy-mcp  
JSON: https://api.skillsregistry.net/v1/skills/sonofakel-raggy-mcp

## Description

Provides centralized, persistent memory and knowledge graph for AI agents via Raggy, enabling recall of decisions, errors, and preferences across sessions.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/e3cj4kgpce)
- **Repository:** <https://github.com/sonofakel/raggy-mcp>

## 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": "sonofakel-raggy-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sonofakel-raggy-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sonofakel-raggy-mcp/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