# mycelium

> mycelium — nxoim-mycelium. Use this tool when you need to implement a simple node-based memory system for AI agents, solving problems related to data storage and retrieval in artificial intelligence applications. It provides a command-line interface, MCP protocol support via stdio and HTTP, and an observation server, accepting input from various sources and outputting stored data. Ideal for use in AI development contexts requiring efficient memory management, such as machine learning model training or knowledge graph construction.

Canonical page: https://skillsregistry.net/skills/nxoim-mycelium  
JSON: https://api.skillsregistry.net/v1/skills/nxoim-mycelium

## Description

Simple node based memory system for AI agents. Built in Swift. CLI, MCP (stdio and HTTP), and observation WebSocket server.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/nxoim/mycelium)

## 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": "nxoim-mycelium"
    }
  }
}
```

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

---
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