# mhn-ai-agent-memory

> mhn-ai-agent-memory — shahzebqazi-mhn-ai-agent-memory. Use this tool when you need to efficiently store and retrieve AI agent memory without relying on large language models or databases. It solves the problem of scalable and fast memory access for AI coding agents like Cursor and Claude Code. The tool takes in AI agent inputs and outputs stored memory states through a simple matrix multiplication interface.

Canonical page: https://skillsregistry.net/skills/shahzebqazi-mhn-ai-agent-memory  
JSON: https://api.skillsregistry.net/v1/skills/shahzebqazi-mhn-ai-agent-memory

## Description

AI agent memory using Modern Hopfield Networks — no LLM calls, no database, one matrix multiply. MCP server for Cursor, Claude Code, and other AI coding agents.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** database
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/shahzebqazi/mhn-ai-agent-memory)

## 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": "shahzebqazi-mhn-ai-agent-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/shahzebqazi-mhn-ai-agent-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/shahzebqazi-mhn-ai-agent-memory/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