# genpark-meta-muse-episodic-memory-graph-mcp

> genpark-meta-muse-episodic-memory-graph-mcp — alphaparkinc-genpark-meta-muse-episodic-memory-graph-mcp. Use this tool when you need to integrate multimodal perception with episodic memory streams to enhance contextual understanding and knowledge retention. It solves problems related to information overload and forgetfulness by fusing ambient data with continuous memory streams and applying recency decay. This tool accepts multimodal inputs and outputs a unified knowledge graph, ideal for applications requiring dynamic memory and context-aware processing.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-meta-muse-episodic-memory-graph-mcp  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-meta-muse-episodic-memory-graph-mcp

## Description

Native Model Context Protocol (MCP) server fusing Meta ambient multimodal perception with Muse continuous episodic memory streams and Ebbinghaus recency decay.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-27

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-meta-muse-episodic-memory-graph-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": "alphaparkinc-genpark-meta-muse-episodic-memory-graph-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-meta-muse-episodic-memory-graph-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-meta-muse-episodic-memory-graph-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
